From ccb09fab30d99e5202d7a740d79992dad4754d34 Mon Sep 17 00:00:00 2001 From: amaiaita <114224821+amaiaita@users.noreply.github.com> Date: Wed, 6 Nov 2024 16:33:09 +0000 Subject: [PATCH 1/7] tag ontology --- docs/our_work/adrenal-lesions.md | 2 +- docs/our_work/ai-deep-dive.md | 2 +- docs/our_work/ai-dictionary.md | 2 +- docs/our_work/ai-ethics.md | 2 +- docs/our_work/ambulance-delay-predictor.md | 2 +- docs/our_work/bed-allocation.md | 2 +- docs/our_work/c245_synpath.md | 2 +- docs/our_work/c338_poud.md | 2 +- docs/our_work/c399_privfinger.md | 2 +- .../casestudy-recruitment-shortlisting.md | 2 +- .../casestudy-synthetic-data-pipeline.md | 2 +- docs/our_work/ct-alignment.md | 2 +- docs/our_work/data-lens.md | 2 +- .../linkage-projects/better-matching.md | 2 +- docs/our_work/ds251_RAG.md | 2 +- docs/our_work/ds255_privacyfp.md | 2 +- docs/our_work/long-stay-baseline.md | 2 +- docs/our_work/long-stay.md | 2 +- docs/our_work/nhs-resolution.md | 2 +- .../nursing-placement-optimisation.md | 2 +- docs/our_work/p11_synpathdiabetes.md | 2 +- docs/our_work/p12_synthvae.md | 2 +- docs/our_work/p14_mcr.md | 2 +- docs/our_work/p21_synthvae.md | 2 +- docs/our_work/p22_txtrayalign.md | 2 +- docs/our_work/p23_stm.md | 2 +- docs/our_work/p31_txtrayalign2.md | 2 +- docs/our_work/p32_phmdiabetes.md | 2 +- docs/our_work/p43_medcat.md | 2 +- docs/our_work/ratings-and-reviews.md | 2 +- docs/our_work/renal-health-prediction.md | 2 +- docs/our_work/sde_data_validation.md | 2 +- docs/our_work/swpclab.md | 2 +- docs/our_work/synthetic-data-pipeline.md | 2 +- docs/our_work/tags.md | 131 +++++++++++++++++- 35 files changed, 164 insertions(+), 35 deletions(-) diff --git a/docs/our_work/adrenal-lesions.md b/docs/our_work/adrenal-lesions.md index 2330fdad..7171a86c 100644 --- a/docs/our_work/adrenal-lesions.md +++ b/docs/our_work/adrenal-lesions.md @@ -3,7 +3,7 @@ title: 'Using deep learning to detect adrenal lesions in CT scans' summary: 'This project explored whether applying AI and deep learning augment the detection of adrenal incidentalomas in patients’ CT scans.' category: 'Projects' origin: 'Skunkworks' -tags: ['CLASSIFICATION','LESION DETECTION','COMPUTER VISION','AI'] +tags: ['CLASSIFICATION','LESION DETECTION','COMPUTER VISION','AI', 'ACCURACY'] ---
diff --git a/docs/our_work/ai-deep-dive.md b/docs/our_work/ai-deep-dive.md index d05c7c24..ac777cf5 100644 --- a/docs/our_work/ai-deep-dive.md +++ b/docs/our_work/ai-deep-dive.md @@ -3,7 +3,7 @@ title: 'AI Deep Dive' summary: 'The NHS AI Lab Skunkworks team have developed and delivered a series of workshops to improve confidence working with AI.' category: 'Playbooks' origin: 'Skunkworks' -tags : ['AI', 'GUIDANCE', 'BEST PRACTICE'] +tags : ['AI', 'BEST PRACTICE'] --- # Case Study diff --git a/docs/our_work/ai-dictionary.md b/docs/our_work/ai-dictionary.md index 707f7131..110e33b7 100644 --- a/docs/our_work/ai-dictionary.md +++ b/docs/our_work/ai-dictionary.md @@ -3,7 +3,7 @@ title: 'AI Dictionary' summary: 'A simple dictionary of common AI terms with a health and care context.' category: 'Projects' origin: 'Skunkworks' -tags : ['AI', 'DICTIONARY', 'JAVASCRIPT', 'REACT'] +tags : ['AI', 'DOCUMENTATION', 'JAVASCRIPT', 'REACT', 'HTML', 'CSS'] --- [![AI Dictionary](../images/ai-dictionary.png)](https://nhsx.github.io/ai-dictionary) diff --git a/docs/our_work/ai-ethics.md b/docs/our_work/ai-ethics.md index 0cb7efcb..b7e46b19 100644 --- a/docs/our_work/ai-ethics.md +++ b/docs/our_work/ai-ethics.md @@ -2,7 +2,7 @@ title: 'AI Ethics in Practice at NHS England' summary: 'Defining ethical AI development best practice for data practitioners in the NHS' origin: 'NHS England' -tags: ['AI', 'ETHICS', 'TRANSPARENCY', 'QUALITY', 'DOCUMENTATION', 'RESEARCH', 'GUIDANCE', 'BEST PRACTICE'] +tags: ['AI', 'ETHICS', 'QUALITY', 'DOCUMENTATION', 'RESEARCH', 'BEST PRACTICE'] --- !!! warning diff --git a/docs/our_work/ambulance-delay-predictor.md b/docs/our_work/ambulance-delay-predictor.md index e2c42b64..5a02de5b 100644 --- a/docs/our_work/ambulance-delay-predictor.md +++ b/docs/our_work/ambulance-delay-predictor.md @@ -3,7 +3,7 @@ title: 'Ambulance Handover Delay Predictor' summary: 'Predict ambulance delays at hospital, with reasons, to allow them to influence hospitals'' behaviour to mitigate against queues before they happen.' category: 'Projects' origin: 'Skunkworks' -tags: ['AMBULANCE','PREDICTION','RANDOM FOREST', 'CLASSIFICATION', 'TIME SERIES', 'PYTHON'] +tags: ['AMBULANCE','FORECASTING','MACHINE LEARNING', 'CLASSIFICATION', 'TIME SERIES', 'PYTHON'] --- ![Ambulance Handover Delay Predictor screenshot](../images/ambulance-delay-predictor.png) diff --git a/docs/our_work/bed-allocation.md b/docs/our_work/bed-allocation.md index 42036d72..0660480b 100644 --- a/docs/our_work/bed-allocation.md +++ b/docs/our_work/bed-allocation.md @@ -3,7 +3,7 @@ title: 'Bed allocation' summary: 'Machine learning to effectively aid bed management in Kettering General Hospital.' category: 'Projects' origin: 'Skunkworks' -tags: ['HOSPITAL','BAYESIAN FORECASTING','MONTE CARLO','GREEDY ALLOCATION', 'PYTHON'] +tags: ['HOSPITAL','FORECASTING','MONTE CARLO','GREEDY ALGORITHM', 'PYTHON', 'JAVASCRIPT', 'HTML', 'CSS'] --- ![Bed allocation screenshot](../images/bed-allocation.png) diff --git a/docs/our_work/c245_synpath.md b/docs/our_work/c245_synpath.md index fbf56584..4574a26c 100644 --- a/docs/our_work/c245_synpath.md +++ b/docs/our_work/c245_synpath.md @@ -3,7 +3,7 @@ title: Building the Foundations for a Generic Patient Simulator summary: Developing an agent-based simulation for generating synthetic patient pathways and scenario modelling for healthcare specific implementations. category: Projects permalink: c245_synpath.html -tags: ['SYNTHETIC DATA', 'PATHWAYS','SIMULATION'] +tags: ['SYNTHETIC DATA','SIMULATION'] --- ![Overview of data model](../images/c245fig1.png) diff --git a/docs/our_work/c338_poud.md b/docs/our_work/c338_poud.md index 768c335e..448f1082 100644 --- a/docs/our_work/c338_poud.md +++ b/docs/our_work/c338_poud.md @@ -2,7 +2,7 @@ title: How to Assess the Privacy of Unstructured Data summary: What are the privacy considerations that need to be addressed when dealing with unstructured healthcare text data permalink: c338_poud.html -tags: ['UNSTRUCTURED DATA', 'PRIVACY', 'PII', 'BEST PRACTICE'] +tags: ['UNSTRUCTURED DATA', 'ETHICS', 'PII', 'BEST PRACTICE', 'STRUCTURED DATA'] ---
diff --git a/docs/our_work/c399_privfinger.md b/docs/our_work/c399_privfinger.md index 87f4fe70..5b861afe 100644 --- a/docs/our_work/c399_privfinger.md +++ b/docs/our_work/c399_privfinger.md @@ -2,7 +2,7 @@ title: Building a Tool to Assess the Privacy Risk of Text Data summary: Can we generate usable privacy scores for text data to support understanding of privacy concerns and the anonymisation process permalink: c399_privfinger.html -tags: ['TEXT DATA', 'LLM','PYTHON', 'PRIVACY'] +tags: ['TEXT DATA', 'LLM','PYTHON', ] --- This work was undertaken as an external commission aiming to build a pipeline of components which firstly generated unstructured medical notes using a structured output from [Synthea:tm:](https://github.com/synthetichealth/synthea) and then running these through [GPT-3.5](https://platform.openai.com/docs/models/gpt-3-5) models to transform these into human readable notes. diff --git a/docs/our_work/casestudy-recruitment-shortlisting.md b/docs/our_work/casestudy-recruitment-shortlisting.md index f0049179..6123089b 100644 --- a/docs/our_work/casestudy-recruitment-shortlisting.md +++ b/docs/our_work/casestudy-recruitment-shortlisting.md @@ -3,7 +3,7 @@ title: 'Examining whether recruitment data can, and should, be used to train AI summary: 'Identify where bias has potential to occur when using machine learning for shortlisting interview candidates and mitigate it' category: 'CaseStudies' origin: 'Skunkworks' -tags: ['NLP', 'NEURAL NETWORKS'] +tags: ['NLP', 'NEURAL NETWORKS', 'SYNTHETIC DATA'] --- ## Info diff --git a/docs/our_work/casestudy-synthetic-data-pipeline.md b/docs/our_work/casestudy-synthetic-data-pipeline.md index a07d9c75..9f6cc805 100644 --- a/docs/our_work/casestudy-synthetic-data-pipeline.md +++ b/docs/our_work/casestudy-synthetic-data-pipeline.md @@ -3,7 +3,7 @@ title: 'Exploring how to create mock patient data (synthetic data) from real pat summary: 'The generation of safe and effective synthetic data to be used in technologies that improve health and social care.' category: 'CaseStudies' origin: 'Skunkworks' -tags: ['SYNTHETIC DATA','VAE','PRIVACY','QUALITY','UTILITY','AI', 'PYTHON'] +tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','QUALITY','AI', 'PYTHON', 'KEDRO'] --- ## Info diff --git a/docs/our_work/ct-alignment.md b/docs/our_work/ct-alignment.md index 35e51df3..38404b49 100644 --- a/docs/our_work/ct-alignment.md +++ b/docs/our_work/ct-alignment.md @@ -3,7 +3,7 @@ title: 'CT Alignment and Lesion Detection' summary: 'A range of classical and machine learning computer vision techniques to align and detect lesions in anonymised CT scans over time from George Eliot Hospital NHS Trust.' category: 'Projects' origin: 'Skunkworks' -tags: ['CT','COMPUTER VISION','IMAGE REGISTRATION','PYTHON'] +tags: ['CT','COMPUTER VISION','IMAGE REGISTRATION','PYTHON', 'ACCURACY] --- ![CT Alignment and Lesion Detection screenshot](../images/ct-alignment.png) diff --git a/docs/our_work/data-lens.md b/docs/our_work/data-lens.md index 21fe7664..886ea9f1 100644 --- a/docs/our_work/data-lens.md +++ b/docs/our_work/data-lens.md @@ -3,7 +3,7 @@ title: 'Data Lens' summary: 'Data Lens brings together information about multiple databases, providing a fast-access search in multiple languages.' category: 'Projects' origin: 'Skunkworks' -tags: ['NLP', 'SEMANTIC SEARCH', 'SCRAPING','JAVASCRIPT','PYTHON'] +tags: ['NLP', 'SCRAPING','JAVASCRIPT','PYTHON', 'HTML','CSS'] --- ![Data Lens screenshot](../images/data-lens.png) diff --git a/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md b/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md index 0f005153..4ae96388 100644 --- a/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md +++ b/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md @@ -3,7 +3,7 @@ title: 'Probabilistic Linkage Model' summary: 'This project is creating a probabilistic linkage model using Splink, in order to improve linkage outcomes, and by extension, patient outcomes. The aim is for this to be used to link data in a range of NHS datasets.' category: 'Projects' origin: 'NHSD' -tags: ['LINKAGE', 'PYTHON', 'PROBABILISTIC MODEL'] +tags: ['LINKAGE', 'PYTHON', 'PROBABILISTIC LINKAGE', 'PII'] --- ## Crafting a model that suits NHS England data linkage needs diff --git a/docs/our_work/ds251_RAG.md b/docs/our_work/ds251_RAG.md index c1390831..456c965d 100644 --- a/docs/our_work/ds251_RAG.md +++ b/docs/our_work/ds251_RAG.md @@ -2,7 +2,7 @@ title: 'Retrieval Augmented Generation' summary: 'Investigating Advanced RAG, collaborating with efforts to evaluate LLM outputs.' origin: '' -tags: ['NLP','LLM','GENAI'] +tags: ['NLP','LLM','AI'] --- diff --git a/docs/our_work/ds255_privacyfp.md b/docs/our_work/ds255_privacyfp.md index d9920704..e405acee 100644 --- a/docs/our_work/ds255_privacyfp.md +++ b/docs/our_work/ds255_privacyfp.md @@ -1,7 +1,7 @@ --- title: "Building a Tool to Assess the Privacy Risk of Text Data - Extended" summary: Can we generate a modular tool to score the privacy risk of healthcare free-text data using open-source LLMs and NERs. -tags: ['TEXT DATA', 'LLM','PYTHON', 'PRIVACY', 'NAMED ENTITY RECOGNITION', 'UNSTRUCTURED DATA'] +tags: ['TEXT DATA', 'LLM','PYTHON', 'ETHICS', 'NLP', 'UNSTRUCTURED DATA', 'SYNTHETIC DATA'] --- !!! warning diff --git a/docs/our_work/long-stay-baseline.md b/docs/our_work/long-stay-baseline.md index 153c6d99..3f6979e2 100644 --- a/docs/our_work/long-stay-baseline.md +++ b/docs/our_work/long-stay-baseline.md @@ -3,7 +3,7 @@ title: 'Long Stayer Risk Stratification Baseline Models' summary: 'Baseline machine learning models using historical data from Gloucestershire Hospitals NHS Foundation Trust to predict how long a patient will stay in hospital upon admission.' category: 'Projects' origin: 'Skunkworks' -tags: ['LOS','RISK MODEL', 'REGRESSION', 'CLASSIFICATION','PYTHON'] +tags: ['LOS', 'REGRESSION', 'CLASSIFICATION','PYTHON', 'RANDOM FOREST', 'SQL', 'F1', 'ACCURACY'] --- Long Stayer risk stratification baseline models was selected as a project to run in tandem with the [Long Stayer Risk Stratification](long-stay.md) project, and started in March 2022. diff --git a/docs/our_work/long-stay.md b/docs/our_work/long-stay.md index 19bda6c7..c6ecd7a2 100644 --- a/docs/our_work/long-stay.md +++ b/docs/our_work/long-stay.md @@ -3,7 +3,7 @@ title: 'Long Stayer Risk Stratification' summary: 'Machine learning using historical data from Gloucestershire Hospitals NHS Foundation Trust to predict how long a patient will stay in hospital upon admission.' category: 'Projects' origin: 'Skunkworks' -tags: ['LOS','NEURAL NETWORKS','RISK MODEL','PYTHON', 'GAN'] +tags: ['LOS','NEURAL NETWORKS','PYTHON', 'GAN', 'SQL', 'HTML', 'CSS', 'JAVASCRIPT', 'STRUCTURED DATA', 'ACCURACY'] --- ![Long Stayer Risk Stratification screenshot](../images/long-stay.png) diff --git a/docs/our_work/nhs-resolution.md b/docs/our_work/nhs-resolution.md index 43f60a9e..0d826633 100644 --- a/docs/our_work/nhs-resolution.md +++ b/docs/our_work/nhs-resolution.md @@ -3,7 +3,7 @@ title: 'Predicting negligence claims with NHS Resolution' summary: 'This project investigated whether it is possible to use machine learning AI to predict the number of claims a trust is likely to receive and learn what drives them in order to improve safety for patients.' category: 'Projects' origin: 'Skunkworks' -tags: ['CLASSIFICATION','PREDICTION', 'AI'] +tags: ['CLASSIFICATION','FORECASTING', 'AI'] --- NHS Resolution provides expertise to the NHS on resolving concerns and disputes. The organisation holds a wealth of historic data around claims, giving insight and valuable data around the causes and impacts of harm. diff --git a/docs/our_work/nursing-placement-optimisation.md b/docs/our_work/nursing-placement-optimisation.md index dd5e6ac3..c5de3dee 100644 --- a/docs/our_work/nursing-placement-optimisation.md +++ b/docs/our_work/nursing-placement-optimisation.md @@ -3,7 +3,7 @@ title: 'Nursing Placement Schedule Optimisation Tool' summary: 'Optimisation problem developed with Imperial College Healthcare Trust to produce optimised schedules for student nurses going on placement within the trust.' category: 'Projects' origin: 'Skunkworks' -tags: ['OPTIMISATION','GENETIC ALGORITHM', 'PYTHON'] +tags: ['GENETIC ALGORITHM', 'PYTHON'] --- This project is an example of the AI Skunkworks team offering capability resources to produce proof-of-concepts which could be applicable to the NHS at large. The project ran from January 2022 to May 2022. diff --git a/docs/our_work/p11_synpathdiabetes.md b/docs/our_work/p11_synpathdiabetes.md index 3206b3ca..eab249c4 100644 --- a/docs/our_work/p11_synpathdiabetes.md +++ b/docs/our_work/p11_synpathdiabetes.md @@ -3,7 +3,7 @@ layout: base summary: Exploration work into incorporating learning into a pathway simulator for diabetes. This work has fed our current SynPathGo project to create synthetic patient pathways and a foundation for agent based modelling in the NHS. title: Applying our SynPath Simulator to a Diabetes Pathway permalink: p11_synpathdiabetes.html -tags: ['SIMULATION'] +tags: ['SIMULATION', 'SYNTHETIC DATA'] ---
diff --git a/docs/our_work/p12_synthvae.md b/docs/our_work/p12_synthvae.md index 8c918101..f86b9969 100644 --- a/docs/our_work/p12_synthvae.md +++ b/docs/our_work/p12_synthvae.md @@ -3,7 +3,7 @@ layout: base summary: The initial creation of a variational autoencoder with differential privacy for generating single table tabular gaussian data. This work demonstrated the feasibility of this approach for healthcare and fed into further interactions of the code base. title: Investigating Differential Privacy in a Variational AutoEncoder for Synthetic Data Generation permalink: p12_synthvae.html -tags: ['VAE', 'SYNTHETIC DATA', 'PYTHON'] +tags: ['NEURAL NETWORKS', 'SYNTHETIC DATA', 'PYTHON'] --- This project investigates the potential suitability of Variational Autoencoders (VAEs) as a synthetic data generation tool in the context of the NHS. To effectively address this direction, this work focussed on four key aspects: quality, privacy, ease of use, and interpretability. diff --git a/docs/our_work/p14_mcr.md b/docs/our_work/p14_mcr.md index 0f77d092..9415645a 100644 --- a/docs/our_work/p14_mcr.md +++ b/docs/our_work/p14_mcr.md @@ -3,7 +3,7 @@ layout: base title: Using Model Class Reliance to Understand the Impact of Commerical Data on Predictions permalink: p14_mcr.html summary: How to assess the value that commercial sales data of over-the-counter prescriptions has on respiratory death predictions -tags: ['MCR', 'PYTHON', 'MORTALITY', 'RESPIRATORY'] +tags: ['MCR', 'PYTHON', 'MORTALITY', 'RESPIRATORY', 'RANDOM FOREST'] --- The primary aim of the project was to apply the novel variable importance technique, [model class reliance](https://papers.nips.cc/paper/2020/hash/fd512441a1a791770a6fa573d688bff5-Abstract.html), to machine learning models which could predict registered respiratory deaths in the UK. The objective was to assess the value of commercial health data in healthcare predictions compared to other available datasets. diff --git a/docs/our_work/p21_synthvae.md b/docs/our_work/p21_synthvae.md index 10ff64da..9cd49e9d 100644 --- a/docs/our_work/p21_synthvae.md +++ b/docs/our_work/p21_synthvae.md @@ -3,7 +3,7 @@ layout: base title: Developing our SynthVAE code permalink: p21_synthvae2.html summary: Improving our variational autoencoder to consider fairness and to run on non-gaussian distributions -tags: ['VAE', 'PYTHON', 'GAUSSIAN MIXTURE MODEL', 'DAG'] +tags: ['NEURAL NETWORKS', 'PYTHON', 'MIXTURE MODEL', 'DAG', 'SYNTHETIC DATA'] --- Continuation of the previous development of our variational autoencoder (VAE) to correct for an error discovered since the last project finished. This error appears when trying to generate data for continuous variables which follow non-Gaussian distributions. Previously, standard scaling had been used to normalise these variables which was causing the non-gaussian variables to be synthesised poorly. This was replaced with a Gaussian mixture model from the RDT python library to scale and transform these variables into ones with a Gaussian distribution. diff --git a/docs/our_work/p22_txtrayalign.md b/docs/our_work/p22_txtrayalign.md index 4341605c..e6ba0523 100644 --- a/docs/our_work/p22_txtrayalign.md +++ b/docs/our_work/p22_txtrayalign.md @@ -3,7 +3,7 @@ layout: base title: TxtRayAlign permalink: p22_txtrayalign.html summary: Generating descriptive text from X-Ray images using contrastive learning on multi-modal data -tags: ['NLP', 'MULTI-MODAL', 'RETRIEVAL', 'CONTRASTIVE-LEARNING', 'PYTHON'] +tags: ['NLP', 'MULTI-MODAL', 'RETRIEVAL', 'DEEP LEARNING', 'PYTHON'] --- ![](../images/p22fig1.png) diff --git a/docs/our_work/p23_stm.md b/docs/our_work/p23_stm.md index b7217cc7..4fbbbb1f 100644 --- a/docs/our_work/p23_stm.md +++ b/docs/our_work/p23_stm.md @@ -3,7 +3,7 @@ layout: base title: Text Analysis using Structural Topic Modelling permalink: p23_stm.html summary: An open reusable tool for topic modelling of survey responses -tags: ['NLP', 'STRUCTURAL TOPIC MODELLING', 'R'] +tags: ['NLP', 'TOPIC MODELLING', 'R'] --- The development of an R code for investigating the topics found in free text survey data using a technique that monitors both the content of the responses but also the metadata (e.g. when the response was made, which organisation the response relates to) in order to support the construction of these topics. diff --git a/docs/our_work/p31_txtrayalign2.md b/docs/our_work/p31_txtrayalign2.md index 0517bcf7..8f47356d 100644 --- a/docs/our_work/p31_txtrayalign2.md +++ b/docs/our_work/p31_txtrayalign2.md @@ -3,7 +3,7 @@ layout: base title: Adding a Clinical Focus to Evaluating Multi-Modal Data Representations permalink: p31_txtrayalign2.html summary: How to validate synthetic text generated from images for healthcare applications. -tags: ['GENERATION', 'NLP', 'MULTI-MODAL', 'PYTHON'] +tags: ['GENERATION', 'NLP', 'MULTI-MODAL', 'PYTHON', 'SYNTHETIC DATA'] --- ![](../images/p31fig1.png) diff --git a/docs/our_work/p32_phmdiabetes.md b/docs/our_work/p32_phmdiabetes.md index 93e00473..235da54b 100644 --- a/docs/our_work/p32_phmdiabetes.md +++ b/docs/our_work/p32_phmdiabetes.md @@ -3,7 +3,7 @@ layout: base title: Inequalities in Diabetes from PHM Data permalink: p32_phmdiabetes.html summary: How to extract inequalities information from linked population health management data -tags: ['LOGISTIC REGRESSION', 'CATBOOST', 'PYTHON'] +tags: ['MACHINE LEARNING', 'CATBOOST', 'PYTHON'] --- ![](../images/p32fig1.png) diff --git a/docs/our_work/p43_medcat.md b/docs/our_work/p43_medcat.md index 517d2a42..8dad5b5c 100644 --- a/docs/our_work/p43_medcat.md +++ b/docs/our_work/p43_medcat.md @@ -3,7 +3,7 @@ layout: base title: Enriching Clinical Coding for Neurology Pathways using MedCAT permalink: p43_medcat.html summary: In collaboration with Lancaster teaching hospital and the University of Lancaster we aim to apply MedCat (an automated named entity recognition with linkage algorithm) to neurology letters to identify related SNOMED CT coding. -tags: ['MEDCAT', 'SNOMED CT', 'NAMED ENTITY RECOGNITION', 'LINKAGE'] +tags: ['MEDCAT', 'NLP', 'LINKAGE'] --- ## Results diff --git a/docs/our_work/ratings-and-reviews.md b/docs/our_work/ratings-and-reviews.md index 4ad91ad0..754546af 100644 --- a/docs/our_work/ratings-and-reviews.md +++ b/docs/our_work/ratings-and-reviews.md @@ -2,7 +2,7 @@ title: "NHS.UK: Automatic Moderation of Ratings & Reviews" summary: "Using NLP to reduce the average moderation time on the NHS.UK website from days to seconds " origin: "" -tags: ["NLP", "AI", "ML", "NHS.UK"] +tags: ["NLP", "AI", "MACHINE LEARNING", "NHS.UK"] --- The NHS.UK website receives around a hundred thousand reviews every year. These reviews need moderating -- there's [a set of NHS policies which need to be applied to these](https://www.nhs.uk/our-policies/comments-policy/#:~:text=Users%20should%20only%20post%20one,service%20will%20not%20be%20published.) before they can be published. diff --git a/docs/our_work/renal-health-prediction.md b/docs/our_work/renal-health-prediction.md index 84adea1f..ffe34b0b 100644 --- a/docs/our_work/renal-health-prediction.md +++ b/docs/our_work/renal-health-prediction.md @@ -3,7 +3,7 @@ title: 'Renal Health Prediction' summary: 'Identifying acute kidney injury (AKI) patients at higher risk of requiring ITU, needing renal support (dialysis), or likely to have a higher potential for mortality.' category: 'Projects' origin: 'Skunkworks' -tags: ['AKI','RNN','DEEP LEARNING', 'TIME SERIES', 'NEURAL NETWORKS', 'PYTHON'] +tags: ['AKI','DEEP LEARNING', 'TIME SERIES', 'NEURAL NETWORKS', 'PYTHON'] --- ![Renal Health Prediction diagram](../images/renal-health-prediction.png) diff --git a/docs/our_work/sde_data_validation.md b/docs/our_work/sde_data_validation.md index 79f2d63b..30ed5a71 100644 --- a/docs/our_work/sde_data_validation.md +++ b/docs/our_work/sde_data_validation.md @@ -2,7 +2,7 @@ title: 'Reusable New Data Product Validation Functions' summary: 'More Efficient, More Consistent Data ​Through Shared Validation Functions' origin: 'NHS England Secure Data Environment Service Data Wranglers' -tags: ['DATA WRANGLERS', 'NHSE_SDE', 'SDE', 'DATA VALIDATION', 'RAP', 'PYTHON'] +tags: ['SDE', 'DATA VALIDATION', 'RAP', 'PYTHON'] --- ![An image showing a stack of boxes on the left and a single box with robotic legs on the right. The stack of boxes has a label "old validation process" along with titles on boxes such as "code not shared", "inconsistent approach", "unreliable" and "manual process". Above the boxes it says "3 days". Next to the boxes an unhappy man is struggling to move them. To the right is a single box with robotic legs, with a happy looking man stood next to it. The box with robotic legs is labeled "new validation process" and has words nearby such as "reusable code", "consistent process" and "easy to re-run". Above the box is a label stating it takes about 30 minutes.](../images/sde_resuable_data_validation_functions.png) diff --git a/docs/our_work/swpclab.md b/docs/our_work/swpclab.md index d891bb9b..d4dce47c 100644 --- a/docs/our_work/swpclab.md +++ b/docs/our_work/swpclab.md @@ -3,7 +3,7 @@ title: "Developing Artificial Primary Care Records" summary: "Creating an artificial longitudinal patient dataset for GPs to trial new technologies in an artificial GP environment." category: "Playbook" origin: "" -tags: ["GENERATION","SYNTHETIC DATA","PYTHON","PRIMARY CARE"] +tags: ["GENERATION","SYNTHETIC DATA","PYTHON","PRIMARY CARE", 'SIMULATION'] --- Primary care records are crucial for understanding healthcare interactions at both the population and individual levels. However, these records are difficult to obtain and integrate with other services, hindering innovation due to data unavailability and privacy concerns. diff --git a/docs/our_work/synthetic-data-pipeline.md b/docs/our_work/synthetic-data-pipeline.md index ad8562b5..b7460de5 100644 --- a/docs/our_work/synthetic-data-pipeline.md +++ b/docs/our_work/synthetic-data-pipeline.md @@ -3,7 +3,7 @@ title: 'Synthetic Data Generation Pipeline' summary: 'Exploring how to create mock patient data from real patient data.' category: 'Playbook' origin: 'Skunkworks' -tags: ['SYNTHETIC DATA','VAE','PRIVACY','KEDRO', 'MIMIC', 'PYTHON'] +tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','KEDRO', 'MIMIC', 'PYTHON'] --- diff --git a/docs/our_work/tags.md b/docs/our_work/tags.md index 6d12c051..efa7d984 100644 --- a/docs/our_work/tags.md +++ b/docs/our_work/tags.md @@ -1 +1,130 @@ -# Projects By Topic \ No newline at end of file +# Project Tags + +Below the tags are sorted by **categories** (Project Status, Data Sources, Coding Libraries & Platforms, Domain Areas, Techniques, Coding Language, Data Types, Evaluation Metrics, and Project Type), however if you would like an **alphabetical list** of all of the tags it can be found [here](#ai) + +
+ +- :material-list-status:{ .lg .middle } __Status__ + + --- + + * [Work in Progress](#WIP) + * [Complete](#complete) + * [On Pause](#paused) + +- :material-table:{ .lg .middle } __Data Sources__ + + --- + + * [MIMIC](#mimic) + * [OpenSafely](#opensafely) + * [Synthetic Data](#synthetic-data) + +- :fontawesome-solid-computer:{ .lg .middle } __Coding Libraries & Platforms__ + + --- + + * [MIMIC](#mimic) + * [CatBoost](#catboosrt) + * [Kedro](#kedro) + * [Medcat](#medcat) + * [Secure Data Environment](#SDE) + * [PyTorch](#pytorch) + * [React.js](#react) + * [Sail](#sail) + * [Trusted Research Environment](#TRE) + +- :material-domain:{ .lg .middle } __Domain Areas__ + + --- + + * [Acute Kidney Injury](#aki) + * [Ambulances](#ambulance) + * [CT](#CT) + * [Hospitals](#hospital) + * [Lesion Detection](#lesion-detection) + * [Length of Stay](#los) + * [Mortality](#mortality) + * [Parkinsons](#parkinsons) + * [Pathology](#pathology) + * [Primary Care](#primary-care) + * [Respiratory](#respiratory) + * [Urgent Care](#urgent-care) + +- :octicons-ai-model-16:{ .lg .middle } __Techniques__ + + --- + + * [AI](#AI) + * [Forecasting](#forecasting) + * [Gradient Boosting](#gradient-boosting) + * [Classification](#classification) + * [Computer Vision](#computer-vision) + * [Deep Learning](#deep-learning) + * [Generative Adversarial Network (GAN)](#gan) + * [Mixture Model](#mixture-model) + * [Genetic Algorithm](#genetic-algorithm) + * [Greedy Algorithm](#greedy-algorithm) + * [Hypergraphs](#hypergraphs) + * [Image Registration](#image-registration) + * [LLM](#LLM) + * [Machine Learning](#machine-learning) + * [Monte Carlo](#monte-carlo) + * [Neural Networks](#neural-networks) + * [Natural Language Processing (NLP)](#NLP) + * [Probabilistic Linkage](#probabilistic-linkage) + * [Random Forest](#random-forest) + * [Regression Models](#regression) + * [Web Scraping](#scraping) + * [Simulation](#simulation) + * [Topic Modelling](#topic-modelling) + * [Direct Acylic Graph](#DAG) + +- :material-projector-screen:{ .lg .middle } __Project Type (exploratory, modeling, etc.)__ + + --- + + * [Best Practice Guidance](#best-practice) + * [Data Validation](#data-validation) + * [Documentation](#documentation) + * [Ethics](#ethics) + * [Explainability](#explainability) + * [Generation](#generation) + * [Linkage](#linkage) + * [Modelling](#modelling) + * [Reproducible Analytical Pipeline (RAP)](#RAP) + * [Research](#research) + +- :material-language-python:{ .lg .middle } __Coding Language__ + + --- + * [Python](#python) + * [SQL](#sql) + * [R](#R) + * [JavaScript](#javascript) + * [HTML](#HTML) + * [CSS](#CSS) + +- :octicons-database-16:{ .lg .middle } __Data Types__ + + --- + + * [Structured](#structured-data) + * [Multi-modal](#multi-modal) + * [Patient Identifiable](#pii) + * [Synthetic](#synthetic-data) + * [Tabular](#tabular-data) + * [Text Data](#text-data) + * [Time Series](#time-series) + * [Unstructured](#unstructured-data) + +- :simple-ticktick:{ .lg .middle } __Evaluation Metrics__ + + --- + + * [F1](#f1) + * [Accuracy](#accuracy) + * [LIME](#LIME) + * [Model Class Reliance](#mcr) + +
\ No newline at end of file From e6909db5526f1ee125c91fa091e8fd577cf70eae Mon Sep 17 00:00:00 2001 From: amaiaita <114224821+amaiaita@users.noreply.github.com> Date: Wed, 13 Nov 2024 12:24:16 +0000 Subject: [PATCH 2/7] implement giulia's feedback --- docs/our_work/a_and_e_forecasting_tool.md | 2 +- docs/our_work/adrenal-lesions.md | 2 +- docs/our_work/ai-deep-dive.md | 2 +- docs/our_work/ai-dictionary.md | 2 +- docs/our_work/ai-ethics.md | 2 +- docs/our_work/ai-skunkworks.md | 2 +- docs/our_work/bed-allocation.md | 2 +- docs/our_work/c339_sas.md | 2 +- .../casestudy-synthetic-data-pipeline.md | 2 +- docs/our_work/ct-alignment.md | 2 +- docs/our_work/data-lens.md | 2 +- .../linkage-projects/better-matching.md | 2 +- docs/our_work/ds251_RAG.md | 2 +- docs/our_work/long-stay-baseline.md | 2 +- docs/our_work/long-stay.md | 2 +- docs/our_work/nhs-resolution.md | 2 +- .../nursing-placement-optimisation.md | 2 +- docs/our_work/p21_synthvae.md | 2 +- docs/our_work/p23_stm.md | 2 +- docs/our_work/p34_hypergraphs.md | 2 +- docs/our_work/p42_hypergraphs2.md | 2 +- docs/our_work/tags.md | 23 ++++--------------- 22 files changed, 25 insertions(+), 40 deletions(-) diff --git a/docs/our_work/a_and_e_forecasting_tool.md b/docs/our_work/a_and_e_forecasting_tool.md index 859c7d17..67dde398 100644 --- a/docs/our_work/a_and_e_forecasting_tool.md +++ b/docs/our_work/a_and_e_forecasting_tool.md @@ -2,7 +2,7 @@ title: 'Accident and Emergency (A&E) Forecasting Tool' summary: 'A probabilistic model which gives a three-week forecast for A&E departments, predicting their expected admissions loads.' origin: '' -tags: ['MODELLING', 'HOSPITAL', 'MONTE CARLO', 'URGENT CARE', ] +tags: ['MODELLING', 'HOSPITAL', 'URGENT CARE' ] --- ![Image showing plot of historical and predicted admissions rates. The plot shows the confidence intervals for the model's fit to historical data, and for its predictions.](../images/a_and_e_forecasting/forecast.png) diff --git a/docs/our_work/adrenal-lesions.md b/docs/our_work/adrenal-lesions.md index 7171a86c..a7e7621d 100644 --- a/docs/our_work/adrenal-lesions.md +++ b/docs/our_work/adrenal-lesions.md @@ -3,7 +3,7 @@ title: 'Using deep learning to detect adrenal lesions in CT scans' summary: 'This project explored whether applying AI and deep learning augment the detection of adrenal incidentalomas in patients’ CT scans.' category: 'Projects' origin: 'Skunkworks' -tags: ['CLASSIFICATION','LESION DETECTION','COMPUTER VISION','AI', 'ACCURACY'] +tags: ['CLASSIFICATION','COMPUTER VISION', 'ACCURACY'] ---
diff --git a/docs/our_work/ai-deep-dive.md b/docs/our_work/ai-deep-dive.md index ac777cf5..cf03902e 100644 --- a/docs/our_work/ai-deep-dive.md +++ b/docs/our_work/ai-deep-dive.md @@ -3,7 +3,7 @@ title: 'AI Deep Dive' summary: 'The NHS AI Lab Skunkworks team have developed and delivered a series of workshops to improve confidence working with AI.' category: 'Playbooks' origin: 'Skunkworks' -tags : ['AI', 'BEST PRACTICE'] +tags : ['BEST PRACTICE'] --- # Case Study diff --git a/docs/our_work/ai-dictionary.md b/docs/our_work/ai-dictionary.md index 110e33b7..67ae1c8e 100644 --- a/docs/our_work/ai-dictionary.md +++ b/docs/our_work/ai-dictionary.md @@ -3,7 +3,7 @@ title: 'AI Dictionary' summary: 'A simple dictionary of common AI terms with a health and care context.' category: 'Projects' origin: 'Skunkworks' -tags : ['AI', 'DOCUMENTATION', 'JAVASCRIPT', 'REACT', 'HTML', 'CSS'] +tags : ['DOCUMENTATION', 'JAVASCRIPT', 'REACT', 'HTML', 'CSS'] --- [![AI Dictionary](../images/ai-dictionary.png)](https://nhsx.github.io/ai-dictionary) diff --git a/docs/our_work/ai-ethics.md b/docs/our_work/ai-ethics.md index b7e46b19..aed37fa5 100644 --- a/docs/our_work/ai-ethics.md +++ b/docs/our_work/ai-ethics.md @@ -2,7 +2,7 @@ title: 'AI Ethics in Practice at NHS England' summary: 'Defining ethical AI development best practice for data practitioners in the NHS' origin: 'NHS England' -tags: ['AI', 'ETHICS', 'QUALITY', 'DOCUMENTATION', 'RESEARCH', 'BEST PRACTICE'] +tags: ['ETHICS', 'QUALITY', 'DOCUMENTATION', 'RESEARCH', 'BEST PRACTICE'] --- !!! warning diff --git a/docs/our_work/ai-skunkworks.md b/docs/our_work/ai-skunkworks.md index 921b948b..3a3ddec2 100644 --- a/docs/our_work/ai-skunkworks.md +++ b/docs/our_work/ai-skunkworks.md @@ -3,7 +3,7 @@ title: 'NHS AI Lab Skunkworks' summary: 'The NHS AI Lab Skunkworks team demonstrates the potential for AI in health and social care through practical experience' category: 'Overview' origin: 'Skunkworks' -tags: ['CLASSIFICATION','LESION DETECTION','AI', 'PYTHON'] +tags: ['CLASSIFICATION', 'PYTHON'] --- !!! info diff --git a/docs/our_work/bed-allocation.md b/docs/our_work/bed-allocation.md index 0660480b..49b2cc30 100644 --- a/docs/our_work/bed-allocation.md +++ b/docs/our_work/bed-allocation.md @@ -3,7 +3,7 @@ title: 'Bed allocation' summary: 'Machine learning to effectively aid bed management in Kettering General Hospital.' category: 'Projects' origin: 'Skunkworks' -tags: ['HOSPITAL','FORECASTING','MONTE CARLO','GREEDY ALGORITHM', 'PYTHON', 'JAVASCRIPT', 'HTML', 'CSS'] +tags: ['HOSPITAL','FORECASTING', 'PYTHON', 'JAVASCRIPT', 'HTML', 'CSS'] --- ![Bed allocation screenshot](../images/bed-allocation.png) diff --git a/docs/our_work/c339_sas.md b/docs/our_work/c339_sas.md index 39ed585b..6bab3f33 100644 --- a/docs/our_work/c339_sas.md +++ b/docs/our_work/c339_sas.md @@ -2,7 +2,7 @@ title: Creating a Generic Adversarial Attack for any Synthetic Dataset summary: Can the privacy of a generated dataset be assessed through downstream adversarial attacks to highlight the risk of re-identification permalink: c339_sas.html -tags: ['SYNTHETIC DATA', 'GAN','TABULAR DATA'] +tags: ['SYNTHETIC DATA','TABULAR DATA'] --- An extensible code was developed to apply a suite of adversarial attacks to synthetically generated single table tabular data in order to assess the likely success of attacks and act as a privacy indicator for the dataset. Using this information then informs the generation and information governance process to ensure the safety of our data. diff --git a/docs/our_work/casestudy-synthetic-data-pipeline.md b/docs/our_work/casestudy-synthetic-data-pipeline.md index 9f6cc805..7dd3fa4c 100644 --- a/docs/our_work/casestudy-synthetic-data-pipeline.md +++ b/docs/our_work/casestudy-synthetic-data-pipeline.md @@ -3,7 +3,7 @@ title: 'Exploring how to create mock patient data (synthetic data) from real pat summary: 'The generation of safe and effective synthetic data to be used in technologies that improve health and social care.' category: 'CaseStudies' origin: 'Skunkworks' -tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','QUALITY','AI', 'PYTHON', 'KEDRO'] +tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','QUALITY','PYTHON', 'KEDRO'] --- ## Info diff --git a/docs/our_work/ct-alignment.md b/docs/our_work/ct-alignment.md index 38404b49..3d39bb37 100644 --- a/docs/our_work/ct-alignment.md +++ b/docs/our_work/ct-alignment.md @@ -3,7 +3,7 @@ title: 'CT Alignment and Lesion Detection' summary: 'A range of classical and machine learning computer vision techniques to align and detect lesions in anonymised CT scans over time from George Eliot Hospital NHS Trust.' category: 'Projects' origin: 'Skunkworks' -tags: ['CT','COMPUTER VISION','IMAGE REGISTRATION','PYTHON', 'ACCURACY] +tags: ['CT','COMPUTER VISION','PYTHON', 'ACCURACY] --- ![CT Alignment and Lesion Detection screenshot](../images/ct-alignment.png) diff --git a/docs/our_work/data-lens.md b/docs/our_work/data-lens.md index 886ea9f1..0885e10a 100644 --- a/docs/our_work/data-lens.md +++ b/docs/our_work/data-lens.md @@ -3,7 +3,7 @@ title: 'Data Lens' summary: 'Data Lens brings together information about multiple databases, providing a fast-access search in multiple languages.' category: 'Projects' origin: 'Skunkworks' -tags: ['NLP', 'SCRAPING','JAVASCRIPT','PYTHON', 'HTML','CSS'] +tags: ['NLP','JAVASCRIPT','PYTHON', 'HTML','CSS'] --- ![Data Lens screenshot](../images/data-lens.png) diff --git a/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md b/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md index 4ae96388..48c5ec04 100644 --- a/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md +++ b/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md @@ -3,7 +3,7 @@ title: 'Probabilistic Linkage Model' summary: 'This project is creating a probabilistic linkage model using Splink, in order to improve linkage outcomes, and by extension, patient outcomes. The aim is for this to be used to link data in a range of NHS datasets.' category: 'Projects' origin: 'NHSD' -tags: ['LINKAGE', 'PYTHON', 'PROBABILISTIC LINKAGE', 'PII'] +tags: ['LINKAGE', 'PYTHON', 'PII'] --- ## Crafting a model that suits NHS England data linkage needs diff --git a/docs/our_work/ds251_RAG.md b/docs/our_work/ds251_RAG.md index 456c965d..89b173b2 100644 --- a/docs/our_work/ds251_RAG.md +++ b/docs/our_work/ds251_RAG.md @@ -2,7 +2,7 @@ title: 'Retrieval Augmented Generation' summary: 'Investigating Advanced RAG, collaborating with efforts to evaluate LLM outputs.' origin: '' -tags: ['NLP','LLM','AI'] +tags: ['NLP','LLM'] --- diff --git a/docs/our_work/long-stay-baseline.md b/docs/our_work/long-stay-baseline.md index 3f6979e2..03882ae5 100644 --- a/docs/our_work/long-stay-baseline.md +++ b/docs/our_work/long-stay-baseline.md @@ -3,7 +3,7 @@ title: 'Long Stayer Risk Stratification Baseline Models' summary: 'Baseline machine learning models using historical data from Gloucestershire Hospitals NHS Foundation Trust to predict how long a patient will stay in hospital upon admission.' category: 'Projects' origin: 'Skunkworks' -tags: ['LOS', 'REGRESSION', 'CLASSIFICATION','PYTHON', 'RANDOM FOREST', 'SQL', 'F1', 'ACCURACY'] +tags: ['LOS', 'REGRESSION', 'CLASSIFICATION','PYTHON', 'SQL', 'F1', 'ACCURACY'] --- Long Stayer risk stratification baseline models was selected as a project to run in tandem with the [Long Stayer Risk Stratification](long-stay.md) project, and started in March 2022. diff --git a/docs/our_work/long-stay.md b/docs/our_work/long-stay.md index c6ecd7a2..3f4dfa92 100644 --- a/docs/our_work/long-stay.md +++ b/docs/our_work/long-stay.md @@ -3,7 +3,7 @@ title: 'Long Stayer Risk Stratification' summary: 'Machine learning using historical data from Gloucestershire Hospitals NHS Foundation Trust to predict how long a patient will stay in hospital upon admission.' category: 'Projects' origin: 'Skunkworks' -tags: ['LOS','NEURAL NETWORKS','PYTHON', 'GAN', 'SQL', 'HTML', 'CSS', 'JAVASCRIPT', 'STRUCTURED DATA', 'ACCURACY'] +tags: ['LOS','NEURAL NETWORKS','PYTHON', 'SQL', 'HTML', 'CSS', 'JAVASCRIPT', 'STRUCTURED DATA', 'ACCURACY'] --- ![Long Stayer Risk Stratification screenshot](../images/long-stay.png) diff --git a/docs/our_work/nhs-resolution.md b/docs/our_work/nhs-resolution.md index 0d826633..53014228 100644 --- a/docs/our_work/nhs-resolution.md +++ b/docs/our_work/nhs-resolution.md @@ -3,7 +3,7 @@ title: 'Predicting negligence claims with NHS Resolution' summary: 'This project investigated whether it is possible to use machine learning AI to predict the number of claims a trust is likely to receive and learn what drives them in order to improve safety for patients.' category: 'Projects' origin: 'Skunkworks' -tags: ['CLASSIFICATION','FORECASTING', 'AI'] +tags: ['CLASSIFICATION','FORECASTING'] --- NHS Resolution provides expertise to the NHS on resolving concerns and disputes. The organisation holds a wealth of historic data around claims, giving insight and valuable data around the causes and impacts of harm. diff --git a/docs/our_work/nursing-placement-optimisation.md b/docs/our_work/nursing-placement-optimisation.md index c5de3dee..48788f22 100644 --- a/docs/our_work/nursing-placement-optimisation.md +++ b/docs/our_work/nursing-placement-optimisation.md @@ -3,7 +3,7 @@ title: 'Nursing Placement Schedule Optimisation Tool' summary: 'Optimisation problem developed with Imperial College Healthcare Trust to produce optimised schedules for student nurses going on placement within the trust.' category: 'Projects' origin: 'Skunkworks' -tags: ['GENETIC ALGORITHM', 'PYTHON'] +tags: ['PYTHON'] --- This project is an example of the AI Skunkworks team offering capability resources to produce proof-of-concepts which could be applicable to the NHS at large. The project ran from January 2022 to May 2022. diff --git a/docs/our_work/p21_synthvae.md b/docs/our_work/p21_synthvae.md index 9cd49e9d..57ca13f3 100644 --- a/docs/our_work/p21_synthvae.md +++ b/docs/our_work/p21_synthvae.md @@ -3,7 +3,7 @@ layout: base title: Developing our SynthVAE code permalink: p21_synthvae2.html summary: Improving our variational autoencoder to consider fairness and to run on non-gaussian distributions -tags: ['NEURAL NETWORKS', 'PYTHON', 'MIXTURE MODEL', 'DAG', 'SYNTHETIC DATA'] +tags: ['NEURAL NETWORKS', 'PYTHON', 'SYNTHETIC DATA'] --- Continuation of the previous development of our variational autoencoder (VAE) to correct for an error discovered since the last project finished. This error appears when trying to generate data for continuous variables which follow non-Gaussian distributions. Previously, standard scaling had been used to normalise these variables which was causing the non-gaussian variables to be synthesised poorly. This was replaced with a Gaussian mixture model from the RDT python library to scale and transform these variables into ones with a Gaussian distribution. diff --git a/docs/our_work/p23_stm.md b/docs/our_work/p23_stm.md index 4fbbbb1f..a19ffddf 100644 --- a/docs/our_work/p23_stm.md +++ b/docs/our_work/p23_stm.md @@ -3,7 +3,7 @@ layout: base title: Text Analysis using Structural Topic Modelling permalink: p23_stm.html summary: An open reusable tool for topic modelling of survey responses -tags: ['NLP', 'TOPIC MODELLING', 'R'] +tags: ['NLP', 'R'] --- The development of an R code for investigating the topics found in free text survey data using a technique that monitors both the content of the responses but also the metadata (e.g. when the response was made, which organisation the response relates to) in order to support the construction of these topics. diff --git a/docs/our_work/p34_hypergraphs.md b/docs/our_work/p34_hypergraphs.md index 49d7b9c2..5d35414b 100644 --- a/docs/our_work/p34_hypergraphs.md +++ b/docs/our_work/p34_hypergraphs.md @@ -3,7 +3,7 @@ layout: base title: Exploring Hypergraphs as a Technique for Understanding Impact of Co-Morbidities permalink: p34_hypergraphs.html summary: In collaboration with Swansea University and the SAIL databank, this work focused on the generation of hypergraphs for investigating the individual and joint impact of comorbidities on a patient pathway. This work will feed into two future projects to continue the creation of directed hypergraphs and then apply graph neural networks to demonstrate the process of extracting useful insights from these data. -tags: ['HYPERGRAPHS', 'SAIL'] +tags: ['SAIL'] --- ## Results diff --git a/docs/our_work/p42_hypergraphs2.md b/docs/our_work/p42_hypergraphs2.md index 9141328a..1e2596ca 100644 --- a/docs/our_work/p42_hypergraphs2.md +++ b/docs/our_work/p42_hypergraphs2.md @@ -3,7 +3,7 @@ layout: base title: Including Mortality in our Implementation of Hypergraphs permalink: p42_hypergraphs2.html summary: A continuation of the previous work on hypergraphs than can extract the impact of predecessor and successor diseases on disease progression pathways. This work in envisaged to include an implicit relationship to demographics and consider the impact of mortality -tags: ['HYPERGRAPHS', 'MORTALITY'] +tags: ['MORTALITY'] --- ## Results diff --git a/docs/our_work/tags.md b/docs/our_work/tags.md index efa7d984..c5b2ad64 100644 --- a/docs/our_work/tags.md +++ b/docs/our_work/tags.md @@ -25,13 +25,13 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin --- * [MIMIC](#mimic) - * [CatBoost](#catboosrt) + * [CatBoost](#catboost) * [Kedro](#kedro) * [Medcat](#medcat) * [Secure Data Environment](#SDE) * [PyTorch](#pytorch) * [React.js](#react) - * [Sail](#sail) + * [SAIL](#sail) * [Trusted Research Environment](#TRE) - :material-domain:{ .lg .middle } __Domain Areas__ @@ -42,7 +42,6 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin * [Ambulances](#ambulance) * [CT](#CT) * [Hospitals](#hospital) - * [Lesion Detection](#lesion-detection) * [Length of Stay](#los) * [Mortality](#mortality) * [Parkinsons](#parkinsons) @@ -55,31 +54,17 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin --- - * [AI](#AI) * [Forecasting](#forecasting) - * [Gradient Boosting](#gradient-boosting) * [Classification](#classification) * [Computer Vision](#computer-vision) * [Deep Learning](#deep-learning) - * [Generative Adversarial Network (GAN)](#gan) - * [Mixture Model](#mixture-model) - * [Genetic Algorithm](#genetic-algorithm) - * [Greedy Algorithm](#greedy-algorithm) - * [Hypergraphs](#hypergraphs) - * [Image Registration](#image-registration) * [LLM](#LLM) * [Machine Learning](#machine-learning) - * [Monte Carlo](#monte-carlo) * [Neural Networks](#neural-networks) * [Natural Language Processing (NLP)](#NLP) - * [Probabilistic Linkage](#probabilistic-linkage) - * [Random Forest](#random-forest) - * [Regression Models](#regression) - * [Web Scraping](#scraping) + * [Linkage](#linkage) * [Simulation](#simulation) - * [Topic Modelling](#topic-modelling) - * [Direct Acylic Graph](#DAG) - + - :material-projector-screen:{ .lg .middle } __Project Type (exploratory, modeling, etc.)__ --- From e25dc8ffe37003f00b7ddaf1efd7c7144124ac9b Mon Sep 17 00:00:00 2001 From: amaiaita <114224821+amaiaita@users.noreply.github.com> Date: Wed, 20 Nov 2024 13:11:48 +0000 Subject: [PATCH 3/7] implement feedback --- docs/our_work/ai-dictionary.md | 2 +- .../casestudy-synthetic-data-pipeline.md | 2 +- docs/our_work/ct-alignment.md | 2 +- docs/our_work/index.md | 2 +- docs/our_work/open-safely.md | 2 +- docs/our_work/p32_phmdiabetes.md | 2 +- docs/our_work/p33_patientsafetylms.md | 2 +- docs/our_work/p34_hypergraphs.md | 2 +- docs/our_work/p43_medcat.md | 2 +- docs/our_work/sde_data_validation.md | 2 +- docs/our_work/synthetic-data-pipeline.md | 2 +- docs/our_work/tags.md | 68 ++++++++----------- 12 files changed, 40 insertions(+), 50 deletions(-) diff --git a/docs/our_work/ai-dictionary.md b/docs/our_work/ai-dictionary.md index 67ae1c8e..382cd768 100644 --- a/docs/our_work/ai-dictionary.md +++ b/docs/our_work/ai-dictionary.md @@ -3,7 +3,7 @@ title: 'AI Dictionary' summary: 'A simple dictionary of common AI terms with a health and care context.' category: 'Projects' origin: 'Skunkworks' -tags : ['DOCUMENTATION', 'JAVASCRIPT', 'REACT', 'HTML', 'CSS'] +tags : ['DOCUMENTATION', 'JAVASCRIPT', 'HTML', 'CSS'] --- [![AI Dictionary](../images/ai-dictionary.png)](https://nhsx.github.io/ai-dictionary) diff --git a/docs/our_work/casestudy-synthetic-data-pipeline.md b/docs/our_work/casestudy-synthetic-data-pipeline.md index 7dd3fa4c..5390b8ca 100644 --- a/docs/our_work/casestudy-synthetic-data-pipeline.md +++ b/docs/our_work/casestudy-synthetic-data-pipeline.md @@ -3,7 +3,7 @@ title: 'Exploring how to create mock patient data (synthetic data) from real pat summary: 'The generation of safe and effective synthetic data to be used in technologies that improve health and social care.' category: 'CaseStudies' origin: 'Skunkworks' -tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','QUALITY','PYTHON', 'KEDRO'] +tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','QUALITY','PYTHON', 'MIMIC'] --- ## Info diff --git a/docs/our_work/ct-alignment.md b/docs/our_work/ct-alignment.md index 3d39bb37..88e1ed73 100644 --- a/docs/our_work/ct-alignment.md +++ b/docs/our_work/ct-alignment.md @@ -3,7 +3,7 @@ title: 'CT Alignment and Lesion Detection' summary: 'A range of classical and machine learning computer vision techniques to align and detect lesions in anonymised CT scans over time from George Eliot Hospital NHS Trust.' category: 'Projects' origin: 'Skunkworks' -tags: ['CT','COMPUTER VISION','PYTHON', 'ACCURACY] +tags: ['CT','COMPUTER VISION','PYTHON', 'ACCURACY'] --- ![CT Alignment and Lesion Detection screenshot](../images/ct-alignment.png) diff --git a/docs/our_work/index.md b/docs/our_work/index.md index fca860d3..f59d9e63 100644 --- a/docs/our_work/index.md +++ b/docs/our_work/index.md @@ -10,7 +10,7 @@ } - [Explore our projects by topic :fontawesome-solid-tags:](./tags.md){ .md-button } + [Explore our projects by categories & tags :fontawesome-solid-tags:](./tags.md){ .md-button }

diff --git a/docs/our_work/open-safely.md b/docs/our_work/open-safely.md index 30f22d99..ee5506fc 100644 --- a/docs/our_work/open-safely.md +++ b/docs/our_work/open-safely.md @@ -3,7 +3,7 @@ title: 'Working with a Trusted Research Environment - the NHS @Home programme' summary: 'An exploration of OpenSafely' category: 'Projects' origin: 'Skunkworks' -tags: ['TRE', 'PYTHON', 'OPENSAFELY'] +tags: ['PYTHON', 'OPENSAFELY'] --- OpenSAFELY gives trusted researchers restricted levels of access to the server to run analysis on real data and obtain aggregate results, without having sight of the patient level data. Aggregate results are checked to ensure there are no disclosure risks before being released from the server. This highly secure way of working enables researchers to have access to large and sensitive datasets in a safe manner. diff --git a/docs/our_work/p32_phmdiabetes.md b/docs/our_work/p32_phmdiabetes.md index 235da54b..4cb15494 100644 --- a/docs/our_work/p32_phmdiabetes.md +++ b/docs/our_work/p32_phmdiabetes.md @@ -3,7 +3,7 @@ layout: base title: Inequalities in Diabetes from PHM Data permalink: p32_phmdiabetes.html summary: How to extract inequalities information from linked population health management data -tags: ['MACHINE LEARNING', 'CATBOOST', 'PYTHON'] +tags: ['MACHINE LEARNING', 'PYTHON'] --- ![](../images/p32fig1.png) diff --git a/docs/our_work/p33_patientsafetylms.md b/docs/our_work/p33_patientsafetylms.md index 516b0f26..8ef62217 100644 --- a/docs/our_work/p33_patientsafetylms.md +++ b/docs/our_work/p33_patientsafetylms.md @@ -3,7 +3,7 @@ layout: base title: Investigating Applying and Evaluating a Language Model to Patient Safety Data permalink: p33_patientsafetylms.html summary: What's the most suitable models and workflows for representing an NHS text dataset? -tags: ['PYTHON', 'NLP', 'LLM', 'PYTORCH'] +tags: ['PYTHON', 'NLP', 'LLM'] --- In collaboration with the NHS England patient safety data team, we present an exploration of a selection of different language model pretraining and finetuning objectives with patient safety incident reports as the domain of interest, followed by a discussion of a number of methods for probing and evaluating these new models, and their respective embedding spaces. diff --git a/docs/our_work/p34_hypergraphs.md b/docs/our_work/p34_hypergraphs.md index 5d35414b..c8d191e9 100644 --- a/docs/our_work/p34_hypergraphs.md +++ b/docs/our_work/p34_hypergraphs.md @@ -3,7 +3,7 @@ layout: base title: Exploring Hypergraphs as a Technique for Understanding Impact of Co-Morbidities permalink: p34_hypergraphs.html summary: In collaboration with Swansea University and the SAIL databank, this work focused on the generation of hypergraphs for investigating the individual and joint impact of comorbidities on a patient pathway. This work will feed into two future projects to continue the creation of directed hypergraphs and then apply graph neural networks to demonstrate the process of extracting useful insights from these data. -tags: ['SAIL'] +tags: [] --- ## Results diff --git a/docs/our_work/p43_medcat.md b/docs/our_work/p43_medcat.md index 8dad5b5c..c5ff8269 100644 --- a/docs/our_work/p43_medcat.md +++ b/docs/our_work/p43_medcat.md @@ -3,7 +3,7 @@ layout: base title: Enriching Clinical Coding for Neurology Pathways using MedCAT permalink: p43_medcat.html summary: In collaboration with Lancaster teaching hospital and the University of Lancaster we aim to apply MedCat (an automated named entity recognition with linkage algorithm) to neurology letters to identify related SNOMED CT coding. -tags: ['MEDCAT', 'NLP', 'LINKAGE'] +tags: ['NLP', 'LINKAGE'] --- ## Results diff --git a/docs/our_work/sde_data_validation.md b/docs/our_work/sde_data_validation.md index 30ed5a71..7aeb26ab 100644 --- a/docs/our_work/sde_data_validation.md +++ b/docs/our_work/sde_data_validation.md @@ -2,7 +2,7 @@ title: 'Reusable New Data Product Validation Functions' summary: 'More Efficient, More Consistent Data ​Through Shared Validation Functions' origin: 'NHS England Secure Data Environment Service Data Wranglers' -tags: ['SDE', 'DATA VALIDATION', 'RAP', 'PYTHON'] +tags: ['DATA VALIDATION', 'RAP', 'PYTHON'] --- ![An image showing a stack of boxes on the left and a single box with robotic legs on the right. The stack of boxes has a label "old validation process" along with titles on boxes such as "code not shared", "inconsistent approach", "unreliable" and "manual process". Above the boxes it says "3 days". Next to the boxes an unhappy man is struggling to move them. To the right is a single box with robotic legs, with a happy looking man stood next to it. The box with robotic legs is labeled "new validation process" and has words nearby such as "reusable code", "consistent process" and "easy to re-run". Above the box is a label stating it takes about 30 minutes.](../images/sde_resuable_data_validation_functions.png) diff --git a/docs/our_work/synthetic-data-pipeline.md b/docs/our_work/synthetic-data-pipeline.md index b7460de5..11e24bc9 100644 --- a/docs/our_work/synthetic-data-pipeline.md +++ b/docs/our_work/synthetic-data-pipeline.md @@ -3,7 +3,7 @@ title: 'Synthetic Data Generation Pipeline' summary: 'Exploring how to create mock patient data from real patient data.' category: 'Playbook' origin: 'Skunkworks' -tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','KEDRO', 'MIMIC', 'PYTHON'] +tags: ['SYNTHETIC DATA','NEURAL NETWORKS','ETHICS','MIMIC', 'PYTHON'] --- diff --git a/docs/our_work/tags.md b/docs/our_work/tags.md index c5b2ad64..9e36a8a6 100644 --- a/docs/our_work/tags.md +++ b/docs/our_work/tags.md @@ -1,6 +1,6 @@ # Project Tags -Below the tags are sorted by **categories** (Project Status, Data Sources, Coding Libraries & Platforms, Domain Areas, Techniques, Coding Language, Data Types, Evaluation Metrics, and Project Type), however if you would like an **alphabetical list** of all of the tags it can be found [here](#ai) +Below the tags are sorted by **categories** (Project Status, Data Sources, Domain Areas, Techniques, Coding Language, Data Types, Evaluation Metrics, and Project Type), however if you would like an **alphabetical list** of all of the tags it can be found [here](#accuracy)

@@ -12,27 +12,30 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin * [Complete](#complete) * [On Pause](#paused) -- :material-table:{ .lg .middle } __Data Sources__ + +- :material-language-python:{ .lg .middle } __Coding Language__ --- - - * [MIMIC](#mimic) - * [OpenSafely](#opensafely) - * [Synthetic Data](#synthetic-data) + * [Python](#python) + * [SQL](#sql) + * [R](#r) + * [JavaScript](#javascript) + * [HTML](#html) + * [CSS](#css) -- :fontawesome-solid-computer:{ .lg .middle } __Coding Libraries & Platforms__ +- :octicons-database-16:{ .lg .middle } __Data Types__ --- - * [MIMIC](#mimic) - * [CatBoost](#catboost) - * [Kedro](#kedro) - * [Medcat](#medcat) - * [Secure Data Environment](#SDE) - * [PyTorch](#pytorch) - * [React.js](#react) - * [SAIL](#sail) - * [Trusted Research Environment](#TRE) + * [Structured](#structured-data) + * [Multi-modal](#multi-modal) + * [Patient Identifiable](#pii) + * [Synthetic](#synthetic-data) + * [Tabular](#tabular-data) + * [Text Data](#text-data) + * [Time Series](#time-series) + * [Unstructured](#unstructured-data) + - :material-domain:{ .lg .middle } __Domain Areas__ @@ -40,7 +43,7 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin * [Acute Kidney Injury](#aki) * [Ambulances](#ambulance) - * [CT](#CT) + * [CT](#ct) * [Hospitals](#hospital) * [Length of Stay](#los) * [Mortality](#mortality) @@ -58,10 +61,10 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin * [Classification](#classification) * [Computer Vision](#computer-vision) * [Deep Learning](#deep-learning) - * [LLM](#LLM) + * [Large Language Models (LLM)](#llm) * [Machine Learning](#machine-learning) * [Neural Networks](#neural-networks) - * [Natural Language Processing (NLP)](#NLP) + * [Natural Language Processing (NLP)](#nlp) * [Linkage](#linkage) * [Simulation](#simulation) @@ -77,31 +80,18 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin * [Generation](#generation) * [Linkage](#linkage) * [Modelling](#modelling) - * [Reproducible Analytical Pipeline (RAP)](#RAP) + * [Reproducible Analytical Pipeline (RAP)](#rap) * [Research](#research) -- :material-language-python:{ .lg .middle } __Coding Language__ - --- - * [Python](#python) - * [SQL](#sql) - * [R](#R) - * [JavaScript](#javascript) - * [HTML](#HTML) - * [CSS](#CSS) -- :octicons-database-16:{ .lg .middle } __Data Types__ +- :material-table:{ .lg .middle } __Data Sources__ --- - - * [Structured](#structured-data) - * [Multi-modal](#multi-modal) - * [Patient Identifiable](#pii) - * [Synthetic](#synthetic-data) - * [Tabular](#tabular-data) - * [Text Data](#text-data) - * [Time Series](#time-series) - * [Unstructured](#unstructured-data) + + * [MIMIC](#mimic) + * [OpenSafely](#opensafely) + * [Synthetic Data](#synthetic-data) - :simple-ticktick:{ .lg .middle } __Evaluation Metrics__ @@ -109,7 +99,7 @@ Below the tags are sorted by **categories** (Project Status, Data Sources, Codin * [F1](#f1) * [Accuracy](#accuracy) - * [LIME](#LIME) + * [LIME](#lime) * [Model Class Reliance](#mcr)
\ No newline at end of file From 16cec433fc774e9d392d424c3b8c5f42cc21784a Mon Sep 17 00:00:00 2001 From: amaiaita <114224821+amaiaita@users.noreply.github.com> Date: Wed, 20 Nov 2024 13:42:38 +0000 Subject: [PATCH 4/7] further improvements --- docs/our_work/a_and_e_forecasting_tool.md | 2 +- .../linkage-projects/better-matching.md | 2 +- .../data-linkage-hub/linkage-projects/cop.md | 2 +- .../linkage-projects/mps-handbook.md | 2 +- .../data-linkage-hub/linkage-projects/qaf.md | 2 +- docs/our_work/index.md | 3 ++- docs/our_work/tags.md | 19 ------------------- overrides/home.html | 3 +-- utils/list-projects.py | 8 ++++++-- 9 files changed, 14 insertions(+), 29 deletions(-) diff --git a/docs/our_work/a_and_e_forecasting_tool.md b/docs/our_work/a_and_e_forecasting_tool.md index 67dde398..24c40b67 100644 --- a/docs/our_work/a_and_e_forecasting_tool.md +++ b/docs/our_work/a_and_e_forecasting_tool.md @@ -2,7 +2,7 @@ title: 'Accident and Emergency (A&E) Forecasting Tool' summary: 'A probabilistic model which gives a three-week forecast for A&E departments, predicting their expected admissions loads.' origin: '' -tags: ['MODELLING', 'HOSPITAL', 'URGENT CARE' ] +tags: ['FORECASTING', 'HOSPITAL', 'URGENT CARE', 'WIP', 'PYTHON'] --- ![Image showing plot of historical and predicted admissions rates. The plot shows the confidence intervals for the model's fit to historical data, and for its predictions.](../images/a_and_e_forecasting/forecast.png) diff --git a/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md b/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md index 48c5ec04..5193133a 100644 --- a/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md +++ b/docs/our_work/data-linkage-hub/linkage-projects/better-matching.md @@ -3,7 +3,7 @@ title: 'Probabilistic Linkage Model' summary: 'This project is creating a probabilistic linkage model using Splink, in order to improve linkage outcomes, and by extension, patient outcomes. The aim is for this to be used to link data in a range of NHS datasets.' category: 'Projects' origin: 'NHSD' -tags: ['LINKAGE', 'PYTHON', 'PII'] +tags: ['LINKAGE', 'PYTHON', 'PII', 'WIP','TABULAR'] --- ## Crafting a model that suits NHS England data linkage needs diff --git a/docs/our_work/data-linkage-hub/linkage-projects/cop.md b/docs/our_work/data-linkage-hub/linkage-projects/cop.md index bd25fb9f..95a747c2 100644 --- a/docs/our_work/data-linkage-hub/linkage-projects/cop.md +++ b/docs/our_work/data-linkage-hub/linkage-projects/cop.md @@ -3,7 +3,7 @@ title: 'Data Linkage Community of Practice (DL CoP)' summary: 'We are creating and leading a community of practice to help people do the best linkage they can, with support from the data linkage team, but also from fellow analysts who are actively working on data linkage.' category: 'Projects' origin: 'NHSD' -tags: ['BEST PRACTICE','EXPLAINABILITY','LINKAGE'] +tags: ['BEST PRACTICE','EXPLAINABILITY','LINKAGE', 'WIP'] --- ## Why do we want a Community of Practice? diff --git a/docs/our_work/data-linkage-hub/linkage-projects/mps-handbook.md b/docs/our_work/data-linkage-hub/linkage-projects/mps-handbook.md index 519c918c..1d4937fa 100644 --- a/docs/our_work/data-linkage-hub/linkage-projects/mps-handbook.md +++ b/docs/our_work/data-linkage-hub/linkage-projects/mps-handbook.md @@ -3,7 +3,7 @@ title: 'MPS Documentation - the Person_ID handbook' summary: 'Documenting how the Person_ID is generated via the Master Person Service (MPS), to make the current process of linking data in the NHS more transparent and easy to understand.' category: 'Projects' origin: 'NHSD' -tags: ['BEST PRACTICE','EXPLAINABILITY','LINKAGE'] +tags: ['BEST PRACTICE','EXPLAINABILITY','LINKAGE', 'COMPLETE'] --- The Person_ID is a unique patient identifier used by NHS England with the objective of standardising the approach to patient-level data linkage across different data sets. diff --git a/docs/our_work/data-linkage-hub/linkage-projects/qaf.md b/docs/our_work/data-linkage-hub/linkage-projects/qaf.md index 8c950f5b..198a1d07 100644 --- a/docs/our_work/data-linkage-hub/linkage-projects/qaf.md +++ b/docs/our_work/data-linkage-hub/linkage-projects/qaf.md @@ -3,7 +3,7 @@ title: 'Quality Assurance Framework for Data Linkage' summary: 'This project aims to create, test, and distribute a quality assurance framework for data linkage to ensure robust, transparent and auditable results.' category: 'Projects' origin: 'NHSD' -tags: ['BEST PRACTICE','EXPLAINABILITY','LINKAGE'] +tags: ['BEST PRACTICE','EXPLAINABILITY','LINKAGE', 'WIP'] --- Data Linkage is a business-critical process within many government organisations, including NHS England. Research publications, official statistics, but also many direct care applications depend on data linkage. Its importance is further amplified when considering privacy preserving principles that require to minimise the use of patients' personal identifiable information. Consequently, data linkage is initiated early in the data lifecycle, establishing a substantial **reliance of downstream applications on the quality of the linkage process**. diff --git a/docs/our_work/index.md b/docs/our_work/index.md index f59d9e63..bb4dc491 100644 --- a/docs/our_work/index.md +++ b/docs/our_work/index.md @@ -2,7 +2,7 @@

Explore our comprehensive portfolio of ongoing and completed projects that harness the power of data to drive insight.