From 0b87a6b19c1435601fc366c4fc8f835db5b2999d Mon Sep 17 00:00:00 2001 From: Alex <67700732+akrztrk@users.noreply.github.com> Date: Mon, 23 Oct 2023 23:17:57 +0200 Subject: [PATCH] md files and release note updated (#726) --- .../2023-06-17-ner_biomarker_pipeline_en.md | 34 +-------- ...2023-06-17-oncology_general_pipeline_en.md | 74 +----------------- ...2023-06-17-oncology_therapy_pipeline_en.md | 36 +-------- ...2023-06-16-oncology_general_pipeline_en.md | 74 +----------------- ...2023-06-16-oncology_general_pipeline_en.md | 76 +------------------ .../licensed_release_notes.md | 35 +-------- .../release_notes_5_1_2.md | 35 +-------- 7 files changed, 9 insertions(+), 355 deletions(-) diff --git a/docs/_posts/C-K-Loan/2023-06-17-ner_biomarker_pipeline_en.md b/docs/_posts/C-K-Loan/2023-06-17-ner_biomarker_pipeline_en.md index 8606c38bad..ede1c793b2 100644 --- a/docs/_posts/C-K-Loan/2023-06-17-ner_biomarker_pipeline_en.md +++ b/docs/_posts/C-K-Loan/2023-06-17-ner_biomarker_pipeline_en.md @@ -34,6 +34,7 @@ This pretrained pipeline is built on the top of [ner_biomarker](https://nlp.john
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python from sparknlp.pretrained import PretrainedPipeline @@ -62,40 +63,10 @@ nlu.load("en.med_ner.biomarker.pipeline").predict("""Here , we report the first
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline - -pipeline = PretrainedPipeline("ner_biomarker_pipeline", "en", "clinical/models") - -text = '''Here , we report the first case of an intraductal tubulopapillary neoplasm of the pancreas with clear cell morphology . Immunohistochemistry revealed positivity for Pan-CK , CK7 , CK8/18 , MUC1 , MUC6 , carbonic anhydrase IX , CD10 , EMA , β-catenin and e-cadherin ''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("ner_biomarker_pipeline", "en", "clinical/models") - -val text = "Here , we report the first case of an intraductal tubulopapillary neoplasm of the pancreas with clear cell morphology . Immunohistochemistry revealed positivity for Pan-CK , CK7 , CK8/18 , MUC1 , MUC6 , carbonic anhydrase IX , CD10 , EMA , β-catenin and e-cadherin " - -val result = pipeline.fullAnnotate(text) -``` - -{:.nlu-block} -```python -import nlu -nlu.load("en.med_ner.biomarker.pipeline").predict("""Here , we report the first case of an intraductal tubulopapillary neoplasm of the pancreas with clear cell morphology . Immunohistochemistry revealed positivity for Pan-CK , CK7 , CK8/18 , MUC1 , MUC6 , carbonic anhydrase IX , CD10 , EMA , β-catenin and e-cadherin """) -``` -
## Results ```bash -Results - - | | ner_chunks | begin | end | ner_label | confidence | |---:|:-------------------------|--------:|------:|:----------------------|-------------:| | 0 | intraductal | 38 | 48 | CancerModifier | 0.9998 | @@ -114,9 +85,6 @@ Results | 13 | EMA | 234 | 236 | Biomarker | 0.9985 | | 14 | β-catenin | 240 | 248 | Biomarker | 0.9948 | | 15 | e-cadherin | 254 | 263 | Biomarker | 0.9952 | - - -{:.model-param} ``` {:.model-param} diff --git a/docs/_posts/C-K-Loan/2023-06-17-oncology_general_pipeline_en.md b/docs/_posts/C-K-Loan/2023-06-17-oncology_general_pipeline_en.md index 1a184e0a62..10570db079 100644 --- a/docs/_posts/C-K-Loan/2023-06-17-oncology_general_pipeline_en.md +++ b/docs/_posts/C-K-Loan/2023-06-17-oncology_general_pipeline_en.md @@ -34,6 +34,7 @@ This pipeline includes Named-Entity Recognition, Assertion Status and Relation E
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python from sparknlp.pretrained import PretrainedPipeline @@ -65,78 +66,13 @@ The tumor is positive for ER and PR.""")
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline - -pipeline = PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -text = '''The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -val text = "The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR." - -val result = pipeline.fullAnnotate(text) -``` -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_general.pipeline").predict("""The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.""") -``` -
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline -pipeline = PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -text = '''The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -val text = "The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR." - -val result = pipeline.fullAnnotate(text) -``` - -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_general.pipeline").predict("""The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.""") -``` -
## Results ```bash -Results - - -Results - - -" ******************** ner_oncology_wip results ******************** | chunk | ner_label | @@ -217,14 +153,6 @@ Results | tumor | Tumor_Finding | PR | Biomarker | O | | positive | Biomarker_Result | ER | Biomarker | is_finding_of | | positive | Biomarker_Result | PR | Biomarker | is_finding_of | - - - - -{:.model-param} - - -{:.model-param} ``` {:.model-param} diff --git a/docs/_posts/C-K-Loan/2023-06-17-oncology_therapy_pipeline_en.md b/docs/_posts/C-K-Loan/2023-06-17-oncology_therapy_pipeline_en.md index 52763b0215..0fb0524c18 100644 --- a/docs/_posts/C-K-Loan/2023-06-17-oncology_therapy_pipeline_en.md +++ b/docs/_posts/C-K-Loan/2023-06-17-oncology_therapy_pipeline_en.md @@ -34,6 +34,7 @@ This pipeline includes Named-Entity Recognition and Assertion Status models to e
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python from sparknlp.pretrained import PretrainedPipeline @@ -62,41 +63,10 @@ nlu.load("en.oncology_therpay.pipeline").predict("""The patient underwent a mast
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline - -pipeline = PretrainedPipeline("oncology_therapy_pipeline", "en", "clinical/models") - -text = '''The patient underwent a mastectomy two years ago. She is currently receiving her second cycle of adriamycin and cyclophosphamide, and is in good overall condition.''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_therapy_pipeline", "en", "clinical/models") - -val text = "The patient underwent a mastectomy two years ago. She is currently receiving her second cycle of adriamycin and cyclophosphamide, and is in good overall condition." - -val result = pipeline.fullAnnotate(text) -``` - -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_therpay.pipeline").predict("""The patient underwent a mastectomy two years ago. She is currently receiving her second cycle of adriamycin and cyclophosphamide, and is in good overall condition.""") -``` -
## Results ```bash -Results - - -" ******************** ner_oncology_wip results ******************** | chunk | ner_label | @@ -153,10 +123,6 @@ Results | mastectomy | Cancer_Surgery | Present_Or_Past | | adriamycin | Chemotherapy | Present_Or_Past | | cyclophosphamide | Chemotherapy | Present_Or_Past | - - - -{:.model-param} ``` {:.model-param} diff --git a/docs/_posts/Cabir40/2023-06-16-oncology_general_pipeline_en.md b/docs/_posts/Cabir40/2023-06-16-oncology_general_pipeline_en.md index 84d837d6b3..172935e428 100644 --- a/docs/_posts/Cabir40/2023-06-16-oncology_general_pipeline_en.md +++ b/docs/_posts/Cabir40/2023-06-16-oncology_general_pipeline_en.md @@ -34,6 +34,7 @@ This pipeline includes Named-Entity Recognition, Assertion Status and Relation E
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python from sparknlp.pretrained import PretrainedPipeline @@ -65,78 +66,13 @@ The tumor is positive for ER and PR.""")
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline - -pipeline = PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -text = '''The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -val text = "The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR." - -val result = pipeline.fullAnnotate(text) -``` -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_general.pipeline").predict("""The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.""") -``` -
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline -pipeline = PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -text = '''The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -val text = "The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR." - -val result = pipeline.fullAnnotate(text) -``` - -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_general.pipeline").predict("""The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.""") -``` -
## Results ```bash -Results - - -Results - - -" ******************** ner_oncology_wip results ******************** | chunk | ner_label | @@ -217,14 +153,6 @@ Results | tumor | Tumor_Finding | PR | Biomarker | O | | positive | Biomarker_Result | ER | Biomarker | is_finding_of | | positive | Biomarker_Result | PR | Biomarker | is_finding_of | - - - - -{:.model-param} - - -{:.model-param} ``` {:.model-param} diff --git a/docs/_posts/ahmedlone127/2023-06-16-oncology_general_pipeline_en.md b/docs/_posts/ahmedlone127/2023-06-16-oncology_general_pipeline_en.md index cbc419abf8..9a2cc2b598 100644 --- a/docs/_posts/ahmedlone127/2023-06-16-oncology_general_pipeline_en.md +++ b/docs/_posts/ahmedlone127/2023-06-16-oncology_general_pipeline_en.md @@ -34,6 +34,7 @@ This pipeline includes Named-Entity Recognition, Assertion Status and Relation E
{% include programmingLanguageSelectScalaPythonNLU.html %} + ```python from sparknlp.pretrained import PretrainedPipeline @@ -65,78 +66,11 @@ The tumor is positive for ER and PR.""")
-
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline - -pipeline = PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -text = '''The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.''' -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -val text = "The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR." - -val result = pipeline.fullAnnotate(text) -``` - -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_general.pipeline").predict("""The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.""") -``` -
- -
-{% include programmingLanguageSelectScalaPythonNLU.html %} -```python -from sparknlp.pretrained import PretrainedPipeline - -pipeline = PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -text = '''The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.''' - -result = pipeline.fullAnnotate(text) -``` -```scala -import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline - -val pipeline = new PretrainedPipeline("oncology_general_pipeline", "en", "clinical/models") - -val text = "The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR." - -val result = pipeline.fullAnnotate(text) -``` - -{:.nlu-block} -```python -import nlu -nlu.load("en.oncology_general.pipeline").predict("""The patient underwent a left mastectomy for a left breast cancer two months ago. -The tumor is positive for ER and PR.""") -``` -
## Results ```bash -Results - - -Results - - -" ******************** ner_oncology_wip results ******************** | chunk | ner_label | @@ -217,14 +151,6 @@ Results | tumor | Tumor_Finding | PR | Biomarker | O | | positive | Biomarker_Result | ER | Biomarker | is_finding_of | | positive | Biomarker_Result | PR | Biomarker | is_finding_of | - - - - -{:.model-param} - - -{:.model-param} ``` {:.model-param} diff --git a/docs/en/spark_nlp_healthcare_versions/licensed_release_notes.md b/docs/en/spark_nlp_healthcare_versions/licensed_release_notes.md index e611400530..cb2c1a2b5d 100644 --- a/docs/en/spark_nlp_healthcare_versions/licensed_release_notes.md +++ b/docs/en/spark_nlp_healthcare_versions/licensed_release_notes.md @@ -84,39 +84,6 @@ These enhancements will elevate your experience with Spark NLP for Healthcare, e | ner_deid_generic_augmented_allUpperCased_langtest | 94.73% | 97.60% | -*Example*: - -```python -clinical_ner = MedicalNerModel.pretrained("ner_clinical_large_langtest", "en", "clinical/models") \ - .setInputCols(["sentence", "token", "embeddings"]) \ - .setOutputCol("ner") - -text= """She was on metformin, glipizide, and dapagliflozin for T2DM and atorvastatin and gemfibrozil for HTG. She had been on dapagliflozin for six months at the time of presentation. Physical examination on presentation was significant for dry oral mucosa; significantly, her abdominal examination was benign with no tenderness, guarding, or rigidity. """ -``` - -*Result*: - -```bash -+-------------------------------------+---------+ -|chunk |ner_label| -+-------------------------------------+---------+ -|metformin |TREATMENT| -|glipizide |TREATMENT| -|dapagliflozin |TREATMENT| -|T2DM |PROBLEM | -|atorvastatin |TREATMENT| -|gemfibrozil |TREATMENT| -|HTG |PROBLEM | -|dapagliflozin |TREATMENT| -|Physical examination |TEST | -|dry oral mucosa |PROBLEM | -|her abdominal examination |TEST | -|tenderness |PROBLEM | -|guarding |PROBLEM | -|rigidity |PROBLEM | -+-------------------------------------+---------+ -``` -
@@ -146,6 +113,7 @@ sample_text = """تاريخ الزيارة: 25 سبتمبر 2023 - المريض ``` *Result*: + |chunk |ner_label| |----------------------------------------------------|-------------------| |مشكل ارتفاع في مستويات في الدم |PROBLEM | @@ -188,6 +156,7 @@ text = [ ``` *Result*: + ```bash +----------------------------------------------------------------------------------------------------+--------------------+ | text| result| diff --git a/docs/en/spark_nlp_healthcare_versions/release_notes_5_1_2.md b/docs/en/spark_nlp_healthcare_versions/release_notes_5_1_2.md index 5a4158109d..d2578f960f 100644 --- a/docs/en/spark_nlp_healthcare_versions/release_notes_5_1_2.md +++ b/docs/en/spark_nlp_healthcare_versions/release_notes_5_1_2.md @@ -84,39 +84,6 @@ These enhancements will elevate your experience with Spark NLP for Healthcare, e | ner_deid_generic_augmented_allUpperCased_langtest | 94.73% | 97.60% | -*Example*: - -```python -clinical_ner = MedicalNerModel.pretrained("ner_clinical_large_langtest", "en", "clinical/models") \ - .setInputCols(["sentence", "token", "embeddings"]) \ - .setOutputCol("ner") - -text= """She was on metformin, glipizide, and dapagliflozin for T2DM and atorvastatin and gemfibrozil for HTG. She had been on dapagliflozin for six months at the time of presentation. Physical examination on presentation was significant for dry oral mucosa; significantly, her abdominal examination was benign with no tenderness, guarding, or rigidity. """ -``` - -*Result*: - -```bash -+-------------------------------------+---------+ -|chunk |ner_label| -+-------------------------------------+---------+ -|metformin |TREATMENT| -|glipizide |TREATMENT| -|dapagliflozin |TREATMENT| -|T2DM |PROBLEM | -|atorvastatin |TREATMENT| -|gemfibrozil |TREATMENT| -|HTG |PROBLEM | -|dapagliflozin |TREATMENT| -|Physical examination |TEST | -|dry oral mucosa |PROBLEM | -|her abdominal examination |TEST | -|tenderness |PROBLEM | -|guarding |PROBLEM | -|rigidity |PROBLEM | -+-------------------------------------+---------+ -``` -
@@ -146,6 +113,7 @@ sample_text = """تاريخ الزيارة: 25 سبتمبر 2023 - المريض ``` *Result*: + |chunk |ner_label| |----------------------------------------------------|-------------------| |مشكل ارتفاع في مستويات في الدم |PROBLEM | @@ -188,6 +156,7 @@ text = [ ``` *Result*: + ```bash +----------------------------------------------------------------------------------------------------+--------------------+ | text| result|