From 5a0b3128bc2a49aecd873c8d49eccfb656d5a0d9 Mon Sep 17 00:00:00 2001 From: Akar <67700732+akrztrk@users.noreply.github.com> Date: Wed, 3 Jan 2024 09:08:56 +0100 Subject: [PATCH] Updated md card and annotators (#844) --- ...2-03-31-drug_action_treatment_mapper_en_3_0.md | 3 +-- ...2-04-04-drug_action_treatment_mapper_en_3_0.md | 2 -- ...-04-normalized_section_header_mapper_en_3_0.md | 7 ------- .../2022-06-07-rxnorm_mapper_en_3_0.md | 3 +-- .../2022-06-24-rxnorm_umls_mapper_en_3_0.md | 1 + ...022-07-06-umls_clinical_drugs_mapper_en_3_0.md | 3 +-- ...-07-08-umls_clinical_findings_mapper_en_3_0.md | 1 + ...2-07-11-umls_disease_syndrome_mapper_en_3_0.md | 1 + ...022-07-11-umls_drug_substance_mapper_en_3_0.md | 3 +-- ...022-07-11-umls_major_concepts_mapper_en_3_0.md | 1 + .../Ahmetemintek/2022-08-23-drug_ade_mapper_en.md | 4 +--- .../2022-09-29-rxnorm_normalized_mapper_en.md | 4 +--- .../2022-09-30-icd10_icd9_mapper_en.md | 6 +----- .../2022-09-30-icd9_icd10_mapper_en.md | 1 + .../Ahmetemintek/2022-09-30-icd9_mapper_en.md | 1 + .../Ahmetemintek/2022-10-12-cvx_code_mapper_en.md | 1 + .../Ahmetemintek/2022-10-12-cvx_name_mapper_en.md | 1 + .../Ahmetemintek/2022-10-29-icd10cm_mapper_en.md | 1 + ...2022-10-30-abbreviation_mapper_augmented_en.md | 1 + .../2022-11-16-abbreviation_category_mapper_en.md | 1 + .../2022-11-18-kegg_disease_mapper_en.md | 1 + .../2022-11-21-kegg_drug_mapper_en.md | 3 +-- .../2023-02-09-rxnorm_drug_brandname_mapper_en.md | 1 - .../2023-02-23-rxnorm_nih_mapper_en.md | 3 +-- .../2023-04-13-hcpcs_ndc_mapper_en.md | 1 + .../2023-04-13-ndc_hcpcs_mapper_en.md | 1 + .../2023-08-08-icd10cm_ms_drg_mapper_en.md | 1 + ...2022-06-26-drug_brandname_ndc_mapper_en_3_0.md | 5 ----- .../2022-06-26-icd10cm_snomed_mapper_en_3_0.md | 3 --- .../2022-06-26-icd10cm_umls_mapper_en_3_0.md | 3 --- .../2022-06-26-icdo_snomed_mapper_en_3_0.md | 2 -- .../2022-06-26-mesh_umls_mapper_en_3_0.md | 2 -- .../2022-06-26-rxnorm_umls_mapper_en_3_0.md | 3 --- .../2022-06-26-snomed_icd10cm_mapper_en_3_0.md | 3 --- .../2022-06-26-snomed_icdo_mapper_en_3_0.md | 3 --- ...06-27-rxnorm_action_treatment_mapper_en_3_0.md | 2 -- .../2022-06-27-rxnorm_mapper_en_3_0.md | 4 +--- .../2022-06-27-rxnorm_ndc_mapper_en_3_0.md | 3 +-- .../2022-06-27-snomed_umls_mapper_en_3_0.md | 3 --- ...2-06-28-drug_action_treatment_mapper_en_3_0.md | 3 --- .../2022-12-18-drug_category_mapper_en.md | 2 -- .../_posts/SKocer/2023-05-30-icd10cm_mapper_en.md | 1 + ...05-08-rxnorm_action_treatment_mapper_en_3_0.md | 4 ---- .../galiph/2022-05-09-rxnorm_ndc_mapper_en_3_0.md | 4 ---- ...2022-05-11-drug_brandname_ndc_mapper_en_3_0.md | 4 ---- .../galiph/2022-05-20-rxnorm_ndc_mapper_en_3_0.md | 3 --- docs/en/licensed_annotator_entries/ChunkMapper.md | 15 +++------------ 47 files changed, 30 insertions(+), 99 deletions(-) diff --git a/docs/_posts/Ahmetemintek/2022-03-31-drug_action_treatment_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-03-31-drug_action_treatment_mapper_en_3_0.md index 0a544c88a9..b44ae21e2f 100644 --- a/docs/_posts/Ahmetemintek/2022-03-31-drug_action_treatment_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-03-31-drug_action_treatment_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drugs with their corresponding `action` and `treatment`. `action` refers to the function of the drug in various body systems, `treatment` refers to which disease the drug is used to treat -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities `action`, `treatment` @@ -39,6 +37,7 @@ This pretrained model maps drugs with their corresponding `action` and `treatmen
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-04-04-drug_action_treatment_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-04-04-drug_action_treatment_mapper_en_3_0.md index 9783474b2d..54b0eaae80 100644 --- a/docs/_posts/Ahmetemintek/2022-04-04-drug_action_treatment_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-04-04-drug_action_treatment_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drugs with their corresponding `action` and `treatment`. `action` refers to the function of the drug in various body systems, `treatment` refers to which disease the drug is used to treat. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities `action`, `treatment` diff --git a/docs/_posts/Ahmetemintek/2022-04-04-normalized_section_header_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-04-04-normalized_section_header_mapper_en_3_0.md index 1d9c860a4b..844df9f9bd 100644 --- a/docs/_posts/Ahmetemintek/2022-04-04-normalized_section_header_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-04-04-normalized_section_header_mapper_en_3_0.md @@ -46,39 +46,32 @@ document_assembler = DocumentAssembler()\ .setInputCol('text')\ .setOutputCol('document') - sentence_detector = SentenceDetector()\ .setInputCols(["document"])\ .setOutputCol("sentence") - tokenizer = Tokenizer()\ .setInputCols("sentence")\ .setOutputCol("token") - embeddings = WordEmbeddingsModel.pretrained("embeddings_clinical", "en","clinical/models")\ .setInputCols(["sentence", "token"])\ .setOutputCol("word_embeddings") - clinical_ner = MedicalNerModel.pretrained("ner_jsl_slim", "en", "clinical/models")\ .setInputCols(["sentence","token", "word_embeddings"])\ .setOutputCol("ner") - ner_converter = NerConverter()\ .setInputCols(["sentence", "token", "ner"])\ .setOutputCol("ner_chunk")\ .setWhiteList(["Header"]) - chunkerMapper = ChunkMapperModel.pretrained("normalized_section_header_mapper", "en", "clinical/models") \ .setInputCols("ner_chunk")\ .setOutputCol("mappings")\ .setRel("level_1") #or level_2 - pipeline = Pipeline().setStages([document_assembler, sentence_detector, tokenizer, diff --git a/docs/_posts/Ahmetemintek/2022-06-07-rxnorm_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-06-07-rxnorm_mapper_en_3_0.md index c883e750bf..8d59d87705 100644 --- a/docs/_posts/Ahmetemintek/2022-06-07-rxnorm_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-06-07-rxnorm_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps entities with their corresponding RxNorm codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities `rxnorm_code` @@ -39,6 +37,7 @@ This pretrained model maps entities with their corresponding RxNorm codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-06-24-rxnorm_umls_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-06-24-rxnorm_umls_mapper_en_3_0.md index 408e904395..895172461a 100644 --- a/docs/_posts/Ahmetemintek/2022-06-24-rxnorm_umls_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-06-24-rxnorm_umls_mapper_en_3_0.md @@ -39,6 +39,7 @@ This pretrained model maps RxNorm codes with corresponding UMLS Codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python documentAssembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2022-07-06-umls_clinical_drugs_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-07-06-umls_clinical_drugs_mapper_en_3_0.md index 483ff11ec3..16977b1291 100644 --- a/docs/_posts/Ahmetemintek/2022-07-06-umls_clinical_drugs_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-07-06-umls_clinical_drugs_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps entities (Clinical Drugs) with their corresponding UMLS CUI codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities `umls_code` @@ -39,6 +37,7 @@ This pretrained model maps entities (Clinical Drugs) with their corresponding UM
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-07-08-umls_clinical_findings_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-07-08-umls_clinical_findings_mapper_en_3_0.md index 7d91b6fc4e..52f386f6bf 100644 --- a/docs/_posts/Ahmetemintek/2022-07-08-umls_clinical_findings_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-07-08-umls_clinical_findings_mapper_en_3_0.md @@ -39,6 +39,7 @@ This pretrained model maps clinical entities and concepts to 4 major categories
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-07-11-umls_disease_syndrome_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-07-11-umls_disease_syndrome_mapper_en_3_0.md index 21c6bb0c07..1b78d39095 100644 --- a/docs/_posts/Ahmetemintek/2022-07-11-umls_disease_syndrome_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-07-11-umls_disease_syndrome_mapper_en_3_0.md @@ -39,6 +39,7 @@ This pretrained model maps entities (Disease or Syndrome) with corresponding UML
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-07-11-umls_drug_substance_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-07-11-umls_drug_substance_mapper_en_3_0.md index c352f73fe8..57c779f9fe 100644 --- a/docs/_posts/Ahmetemintek/2022-07-11-umls_drug_substance_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-07-11-umls_drug_substance_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps entities (Drug Substances) with their corresponding UMLS CUI codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities `umls_code` @@ -39,6 +37,7 @@ This pretrained model maps entities (Drug Substances) with their corresponding U
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-07-11-umls_major_concepts_mapper_en_3_0.md b/docs/_posts/Ahmetemintek/2022-07-11-umls_major_concepts_mapper_en_3_0.md index 967220f54a..af03b6c786 100644 --- a/docs/_posts/Ahmetemintek/2022-07-11-umls_major_concepts_mapper_en_3_0.md +++ b/docs/_posts/Ahmetemintek/2022-07-11-umls_major_concepts_mapper_en_3_0.md @@ -40,6 +40,7 @@ This pretrained model maps entities (Major Clinical Concepts) with corresponding
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-08-23-drug_ade_mapper_en.md b/docs/_posts/Ahmetemintek/2022-08-23-drug_ade_mapper_en.md index 8ec138bb81..ba629372eb 100644 --- a/docs/_posts/Ahmetemintek/2022-08-23-drug_ade_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-08-23-drug_ade_mapper_en.md @@ -22,9 +22,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drugs with their corresponding Adverse Drug Events. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `ADE` @@ -41,6 +38,7 @@ This pretrained model maps drugs with their corresponding Adverse Drug Events.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-09-29-rxnorm_normalized_mapper_en.md b/docs/_posts/Ahmetemintek/2022-09-29-rxnorm_normalized_mapper_en.md index 6e92b7135e..1ccabbdb61 100644 --- a/docs/_posts/Ahmetemintek/2022-09-29-rxnorm_normalized_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-09-29-rxnorm_normalized_mapper_en.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained pipeline maps entities with their corresponding RxNorm codes and normalized RxNorm resolutions. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `rxnorm_code`, `normalized_name` @@ -40,6 +37,7 @@ This pretrained pipeline maps entities with their corresponding RxNorm codes and
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-09-30-icd10_icd9_mapper_en.md b/docs/_posts/Ahmetemintek/2022-09-30-icd10_icd9_mapper_en.md index ffcc126181..724740732a 100644 --- a/docs/_posts/Ahmetemintek/2022-09-30-icd10_icd9_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-09-30-icd10_icd9_mapper_en.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps ICD-10-CM codes to corresponding ICD-9-CM codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `icd9_code` @@ -36,10 +33,9 @@ This pretrained model maps ICD-10-CM codes to corresponding ICD-9-CM codes. ## How to use - -
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python documentAssembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2022-09-30-icd9_icd10_mapper_en.md b/docs/_posts/Ahmetemintek/2022-09-30-icd9_icd10_mapper_en.md index 2c61752ca1..7ccbd5befd 100644 --- a/docs/_posts/Ahmetemintek/2022-09-30-icd9_icd10_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-09-30-icd9_icd10_mapper_en.md @@ -40,6 +40,7 @@ This pretrained model maps ICD-9-CM codes to corresponding ICD-10-CM codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2022-09-30-icd9_mapper_en.md b/docs/_posts/Ahmetemintek/2022-09-30-icd9_mapper_en.md index e6bf99a60e..bf2968c44d 100644 --- a/docs/_posts/Ahmetemintek/2022-09-30-icd9_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-09-30-icd9_mapper_en.md @@ -39,6 +39,7 @@ This pretrained model maps entities with their corresponding ICD-9-CM codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-10-12-cvx_code_mapper_en.md b/docs/_posts/Ahmetemintek/2022-10-12-cvx_code_mapper_en.md index f48138ddad..171b3a7199 100644 --- a/docs/_posts/Ahmetemintek/2022-10-12-cvx_code_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-10-12-cvx_code_mapper_en.md @@ -40,6 +40,7 @@ This pretrained model maps CVX codes with their corresponding vaccine names and
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-10-12-cvx_name_mapper_en.md b/docs/_posts/Ahmetemintek/2022-10-12-cvx_name_mapper_en.md index 6c9486c573..ff4210e242 100644 --- a/docs/_posts/Ahmetemintek/2022-10-12-cvx_name_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-10-12-cvx_name_mapper_en.md @@ -40,6 +40,7 @@ This pretrained model maps vaccine products with their corresponding CVX codes,
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-10-29-icd10cm_mapper_en.md b/docs/_posts/Ahmetemintek/2022-10-29-icd10cm_mapper_en.md index 6b8141a7f7..c422f147ca 100644 --- a/docs/_posts/Ahmetemintek/2022-10-29-icd10cm_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-10-29-icd10cm_mapper_en.md @@ -40,6 +40,7 @@ This pretrained model maps entities with their corresponding ICD-10-CM codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2022-10-30-abbreviation_mapper_augmented_en.md b/docs/_posts/Ahmetemintek/2022-10-30-abbreviation_mapper_augmented_en.md index 8de5ed5ab5..b3eafa8737 100644 --- a/docs/_posts/Ahmetemintek/2022-10-30-abbreviation_mapper_augmented_en.md +++ b/docs/_posts/Ahmetemintek/2022-10-30-abbreviation_mapper_augmented_en.md @@ -40,6 +40,7 @@ This pretrained model maps abbreviations and acronyms of medical regulatory acti
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2022-11-16-abbreviation_category_mapper_en.md b/docs/_posts/Ahmetemintek/2022-11-16-abbreviation_category_mapper_en.md index e002ec6970..8cee23c906 100644 --- a/docs/_posts/Ahmetemintek/2022-11-16-abbreviation_category_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-11-16-abbreviation_category_mapper_en.md @@ -40,6 +40,7 @@ This pretrained model maps abbreviations and acronyms of medical regulatory acti
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2022-11-18-kegg_disease_mapper_en.md b/docs/_posts/Ahmetemintek/2022-11-18-kegg_disease_mapper_en.md index e5dd685fa9..c458e2fecb 100644 --- a/docs/_posts/Ahmetemintek/2022-11-18-kegg_disease_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-11-18-kegg_disease_mapper_en.md @@ -40,6 +40,7 @@ This pretrained model maps diseases with their corresponding `category`, `descri
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2022-11-21-kegg_drug_mapper_en.md b/docs/_posts/Ahmetemintek/2022-11-21-kegg_drug_mapper_en.md index 3675211503..2c8f44556d 100644 --- a/docs/_posts/Ahmetemintek/2022-11-21-kegg_drug_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2022-11-21-kegg_drug_mapper_en.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drugs with their corresponding `efficacy`, `molecular_weight` as well as `CAS`, `PubChem`, `ChEBI`, `LigandBox`, `NIKKAJI`, `PDB-CCD` codes. This model was trained with the data from the KEGG database. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities @@ -40,6 +38,7 @@ This pretrained model maps drugs with their corresponding `efficacy`, `molecular
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2023-02-09-rxnorm_drug_brandname_mapper_en.md b/docs/_posts/Ahmetemintek/2023-02-09-rxnorm_drug_brandname_mapper_en.md index cf9cf91855..b55c8113db 100644 --- a/docs/_posts/Ahmetemintek/2023-02-09-rxnorm_drug_brandname_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2023-02-09-rxnorm_drug_brandname_mapper_en.md @@ -21,7 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RxNorm and RxNorm Extension codes with their corresponding drug brand names. It returns 2 types of brand names for the corresponding RxNorm or RxNorm Extension code. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. ## Predicted Entities diff --git a/docs/_posts/Ahmetemintek/2023-02-23-rxnorm_nih_mapper_en.md b/docs/_posts/Ahmetemintek/2023-02-23-rxnorm_nih_mapper_en.md index a9ac01e573..af8d9a6782 100644 --- a/docs/_posts/Ahmetemintek/2023-02-23-rxnorm_nih_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2023-02-23-rxnorm_nih_mapper_en.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps entities with their corresponding RxNorm codes according to the National Institute of Health (NIH) database. It returns Rxnorm codes with their NIH Rxnorm Term Types within a parenthesis. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities @@ -40,6 +38,7 @@ This pretrained model maps entities with their corresponding RxNorm codes accord
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Ahmetemintek/2023-04-13-hcpcs_ndc_mapper_en.md b/docs/_posts/Ahmetemintek/2023-04-13-hcpcs_ndc_mapper_en.md index 676fd40a5a..834208e9bb 100644 --- a/docs/_posts/Ahmetemintek/2023-04-13-hcpcs_ndc_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2023-04-13-hcpcs_ndc_mapper_en.md @@ -39,6 +39,7 @@ This pretrained model maps HCPCS codes with their corresponding National Drug Co
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2023-04-13-ndc_hcpcs_mapper_en.md b/docs/_posts/Ahmetemintek/2023-04-13-ndc_hcpcs_mapper_en.md index 9a4a2ce274..ed617b58fe 100644 --- a/docs/_posts/Ahmetemintek/2023-04-13-ndc_hcpcs_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2023-04-13-ndc_hcpcs_mapper_en.md @@ -39,6 +39,7 @@ This pretrained model maps National Drug Codes (NDC) with their corresponding HC
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Ahmetemintek/2023-08-08-icd10cm_ms_drg_mapper_en.md b/docs/_posts/Ahmetemintek/2023-08-08-icd10cm_ms_drg_mapper_en.md index a91b076c4c..48280f08de 100644 --- a/docs/_posts/Ahmetemintek/2023-08-08-icd10cm_ms_drg_mapper_en.md +++ b/docs/_posts/Ahmetemintek/2023-08-08-icd10cm_ms_drg_mapper_en.md @@ -39,6 +39,7 @@ This pretrained model maps ICD-10-CM codes with their corresponding Medicare Sev
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-drug_brandname_ndc_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-drug_brandname_ndc_mapper_en_3_0.md index a8dd322742..14dfe25691 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-drug_brandname_ndc_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-drug_brandname_ndc_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drug brand names to corresponding National Drug Codes (NDC). Product NDCs for each strength are returned in result and metadata. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `Strength_NDC` @@ -36,8 +33,6 @@ This pretrained model maps drug brand names to corresponding National Drug Codes ## How to use - -
{% include programmingLanguageSelectScalaPythonNLU.html %} diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_snomed_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_snomed_mapper_en_3_0.md index 16b44731a0..709bac2a0d 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_snomed_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_snomed_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps ICD10-CM codes to corresponding SNOMED codes under the Unified Medical Language System (UMLS). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `snomed_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_umls_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_umls_mapper_en_3_0.md index ca1dd4f317..cf4d1938ec 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_umls_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_umls_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps ICD10CM codes to corresponding UMLS codes under the Unified Medical Language System (UMLS). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `umls_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-icdo_snomed_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-icdo_snomed_mapper_en_3_0.md index 5849afa86e..f1006156ef 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-icdo_snomed_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-icdo_snomed_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps ICDO codes to corresponding SNOMED codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-mesh_umls_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-mesh_umls_mapper_en_3_0.md index ecd01ef3c1..6aaf33c1a0 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-mesh_umls_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-mesh_umls_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps MESH codes to corresponding UMLS codes under the Unified Medical Language System (UMLS). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities `umls_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-rxnorm_umls_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-rxnorm_umls_mapper_en_3_0.md index f4ab5df152..2e7da979de 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-rxnorm_umls_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-rxnorm_umls_mapper_en_3_0.md @@ -20,9 +20,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RXNORM codes to corresponding UMLS codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `umls_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icd10cm_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icd10cm_mapper_en_3_0.md index 6ecec4082a..b7c3193cb7 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icd10cm_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icd10cm_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps SNOMED codes to corresponding ICD10-CM codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `icd10cm_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icdo_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icdo_mapper_en_3_0.md index f30bf06d3e..a8946da83c 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icdo_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icdo_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps SNOMED codes to corresponding ICDO codes under the Unified Medical Language System (UMLS). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `icdo_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_action_treatment_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_action_treatment_mapper_en_3_0.md index b171ed3f2b..be815f6273 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_action_treatment_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_action_treatment_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RxNorm and RxNorm Extension codes with their corresponding action and treatment. Action refers to the function of the drug in various body systems; treatment refers to which disease the drug is used to treat. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities diff --git a/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_mapper_en_3_0.md index 4ff7081cce..10b464f508 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps entities with their corresponding RxNorm codes. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `rxnorm_code` @@ -40,6 +37,7 @@ This pretrained model maps entities with their corresponding RxNorm codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol('text')\ diff --git a/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_ndc_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_ndc_mapper_en_3_0.md index b4f1d1712b..9a29eaa90c 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_ndc_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-27-rxnorm_ndc_mapper_en_3_0.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RxNorm and RxNorm Extension codes with corresponding National Drug Codes (NDC). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities @@ -40,6 +38,7 @@ This pretrained model maps RxNorm and RxNorm Extension codes with corresponding
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python documentAssembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/Damla-Gurbaz/2022-06-27-snomed_umls_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-27-snomed_umls_mapper_en_3_0.md index 1b7a7528d4..382229e630 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-27-snomed_umls_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-27-snomed_umls_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps SNOMED codes to corresponding UMLS codes under the Unified Medical Language System (UMLS). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `umls_code` diff --git a/docs/_posts/Damla-Gurbaz/2022-06-28-drug_action_treatment_mapper_en_3_0.md b/docs/_posts/Damla-Gurbaz/2022-06-28-drug_action_treatment_mapper_en_3_0.md index 7b3767ecdb..9c4e20bf76 100644 --- a/docs/_posts/Damla-Gurbaz/2022-06-28-drug_action_treatment_mapper_en_3_0.md +++ b/docs/_posts/Damla-Gurbaz/2022-06-28-drug_action_treatment_mapper_en_3_0.md @@ -21,9 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drugs with their corresponding action and treatment. action refers to the function of the drug in various body systems, treatment refers to which disease the drug is used to treat. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `action`, `treatment` diff --git a/docs/_posts/Damla-Gurbaz/2022-12-18-drug_category_mapper_en.md b/docs/_posts/Damla-Gurbaz/2022-12-18-drug_category_mapper_en.md index db6e628f6d..6a8132cd5d 100644 --- a/docs/_posts/Damla-Gurbaz/2022-12-18-drug_category_mapper_en.md +++ b/docs/_posts/Damla-Gurbaz/2022-12-18-drug_category_mapper_en.md @@ -21,8 +21,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drugs to their categories and other brands and names. It has two categories called main category and subcategory. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - ## Predicted Entities diff --git a/docs/_posts/SKocer/2023-05-30-icd10cm_mapper_en.md b/docs/_posts/SKocer/2023-05-30-icd10cm_mapper_en.md index 3401df16e8..c838c2947c 100644 --- a/docs/_posts/SKocer/2023-05-30-icd10cm_mapper_en.md +++ b/docs/_posts/SKocer/2023-05-30-icd10cm_mapper_en.md @@ -39,6 +39,7 @@ This pretrained model maps entities with their corresponding ICD-10-CM codes.
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python document_assembler = DocumentAssembler()\ .setInputCol("text")\ diff --git a/docs/_posts/galiph/2022-05-08-rxnorm_action_treatment_mapper_en_3_0.md b/docs/_posts/galiph/2022-05-08-rxnorm_action_treatment_mapper_en_3_0.md index 21ce06f143..8edfe3933f 100644 --- a/docs/_posts/galiph/2022-05-08-rxnorm_action_treatment_mapper_en_3_0.md +++ b/docs/_posts/galiph/2022-05-08-rxnorm_action_treatment_mapper_en_3_0.md @@ -23,10 +23,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RxNorm and RxNorm Extension codes with their corresponding action and treatment. Action refers to the function of the drug in various body systems; treatment refers to which disease the drug is used to treat. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - - ## Predicted Entities diff --git a/docs/_posts/galiph/2022-05-09-rxnorm_ndc_mapper_en_3_0.md b/docs/_posts/galiph/2022-05-09-rxnorm_ndc_mapper_en_3_0.md index 0e0093c720..b2f63a4197 100644 --- a/docs/_posts/galiph/2022-05-09-rxnorm_ndc_mapper_en_3_0.md +++ b/docs/_posts/galiph/2022-05-09-rxnorm_ndc_mapper_en_3_0.md @@ -23,10 +23,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RxNorm and RxNorm Extension codes with corresponding National Drug Codes (NDC). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - - ## Predicted Entities diff --git a/docs/_posts/galiph/2022-05-11-drug_brandname_ndc_mapper_en_3_0.md b/docs/_posts/galiph/2022-05-11-drug_brandname_ndc_mapper_en_3_0.md index 8ff76c9532..6cffba0911 100644 --- a/docs/_posts/galiph/2022-05-11-drug_brandname_ndc_mapper_en_3_0.md +++ b/docs/_posts/galiph/2022-05-11-drug_brandname_ndc_mapper_en_3_0.md @@ -23,10 +23,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps drug brand names to corresponding National Drug Codes (NDC). Product NDCs for each strength are returned in result and metadata. -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - - ## Predicted Entities diff --git a/docs/_posts/galiph/2022-05-20-rxnorm_ndc_mapper_en_3_0.md b/docs/_posts/galiph/2022-05-20-rxnorm_ndc_mapper_en_3_0.md index ee975004c5..8bba75d6c8 100644 --- a/docs/_posts/galiph/2022-05-20-rxnorm_ndc_mapper_en_3_0.md +++ b/docs/_posts/galiph/2022-05-20-rxnorm_ndc_mapper_en_3_0.md @@ -20,9 +20,6 @@ use_language_switcher: "Python-Scala-Java" This pretrained model maps RxNorm and RxNorm Extension codes with corresponding National Drug Codes (NDC). -`Important Note`: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains 'Mapper', it is necessary to use the ChunkMapperModel after an EntityResolverModel. - - ## Predicted Entities `Product NDC`, `Package NDC` diff --git a/docs/en/licensed_annotator_entries/ChunkMapper.md b/docs/en/licensed_annotator_entries/ChunkMapper.md index 09fea5a987..a026fa8696 100644 --- a/docs/en/licensed_annotator_entries/ChunkMapper.md +++ b/docs/en/licensed_annotator_entries/ChunkMapper.md @@ -674,11 +674,6 @@ model.stages[-1].write().save("models/legal_mapper") {%- endcapture -%} {%- capture approach_scala_medical -%} - -{%- endcapture -%} - -{%- capture approach_scala_finance -%} - import spark.implicits._ val document_assembler = new DocumentAssembler() @@ -729,11 +724,9 @@ val model = pipeline.fit(test_data) res= model.transform(test_data) model.stagesArray(-1) .write() .save("models/drug_mapper") - {%- endcapture -%} -{%- capture approach_python_finance -%} - +{%- capture approach_scala_finance -%} import spark.implicits._ val document_assembler = new DocumentAssembler() @@ -785,11 +778,9 @@ val model = pipeline.fit(test_data) res= model.transform(test_data) model.stagesArray(-1) .write() .save("models/finance_mapper") - {%- endcapture -%} {%- capture approach_scala_legal -%} - import spark.implicits._ val document_assembler = new DocumentAssembler() @@ -839,8 +830,8 @@ val model = pipeline.fit(test_data) res= model.transform(test_data) model.stagesArray(-1) .write() .save("models/legal_mapper") - {%- endcapture -%} + {%- capture approach_api_link -%} [ChunkMapperApproach](https://nlp.johnsnowlabs.com/licensed/api/com/johnsnowlabs/finance/chunk_classification/resolution/ChunkMapperApproach.html) {%- endcapture -%} @@ -850,7 +841,7 @@ model.stagesArray(-1) .write() .save("models/legal_mapper") {%- endcapture -%} {%- capture approach_notebook_link -%} -[ChunkMapperApproachModel](https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/Healthcare_MOOC/Spark_NLP_Udemy_MOOC/Healthcare_NLP/ChunkMapperApproach.ipynb) +[ChunkMapperApproachModelNotebook](https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/Healthcare_MOOC/Spark_NLP_Udemy_MOOC/Healthcare_NLP/ChunkMapperApproach.ipynb) {%- endcapture -%} {% include templates/licensed_approach_model_medical_fin_leg_template.md