updated md cards (#860)

JohnSnowLabs · Jan 11, 2024 · 7291d59 · 7291d59
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diff --git a/docs/_posts/C-K-Loan/2023-06-17-explain_clinical_doc_medication_en.md b/docs/_posts/C-K-Loan/2023-06-17-explain_clinical_doc_medication_en.md
@@ -68,6 +68,7 @@ nlu.load("en.explain_dco.clinical_medication.pipeline").predict("""The patient i
 ## Results
 
 ```bash
+# ner_chunk
 +----+----------------+------------+
 |    | chunks         | entities   |
 |---:|:---------------|:-----------|
@@ -84,15 +85,17 @@ nlu.load("en.explain_dco.clinical_medication.pipeline").predict("""The patient i
 | 10 | at bedtime     | FREQUENCY  |
 +----+----------------+------------+
 
-+----+----------+------------+-------------+
-|    | chunks   | entities   | assertion   |
-|---:|:---------|:-----------|:------------|
-|  0 | insulin  | DRUG       | Present     |
-|  1 | Bactrim  | DRUG       | Past        |
-|  2 | Fragmin  | DRUG       | Planned     |
-|  3 | Lantus   | DRUG       | Planned     |
-+----+----------+------------+-------------+
-
+# assertion
++---+---------+----------+-----------+
+|   |  chunks | entities | assertion |
+|--:|--------:|---------:|----------:|
+| 0 | insulin |     DRUG |    Family |
+| 1 | Bactrim |     DRUG |      Past |
+| 2 | Fragmin |     DRUG |   Planned |
+| 3 |  Lantus |     DRUG |      Past |
++---+---------+----------+-----------+
+
+# relation
 +----------------+-----------+------------+-----------+----------------+
 | relation       | entity1   | chunk1     | entity2   | chunk2         |
 |:---------------|:----------|:-----------|:----------|:---------------|

diff --git a/docs/_posts/C-K-Loan/2023-06-17-re_bodypart_proceduretest_pipeline_en.md b/docs/_posts/C-K-Loan/2023-06-17-re_bodypart_proceduretest_pipeline_en.md
@@ -64,9 +64,14 @@ nlu.load("en.relation.bodypart_proceduretest.pipeline").predict("""TECHNIQUE IN
 ## Results
 
 ```bash
-| index | relations | entity1                      | entity1_begin | entity1_end | chunk1 | entity2 | entity2_end | entity2_end | chunk2              | confidence |
-|-------|-----------|------------------------------|---------------|-------------|--------|---------|-------------|-------------|---------------------|------------|
-| 0     | 1         | External_body_part_or_region | 94            | 98          | chest  | Test    | 117         | 135         | portable ultrasound | 1.0        |
+|   | sentence | entity1_begin | entity1_end |               chunk1 |                      entity1 | entity2_begin | entity2_end |              chunk2 |                      entity2 | relation | confidence |
+|--:|---------:|--------------:|------------:|---------------------:|-----------------------------:|--------------:|------------:|--------------------:|-----------------------------:|---------:|-----------:|
+| 0 |        0 |             0 |          19 | TECHNIQUE IN DETAIL: |               Section_Header |            78 |          87 |          his mother |                       Gender |        1 |  0.9999987 |
+| 1 |        0 |             0 |          19 | TECHNIQUE IN DETAIL: |               Section_Header |            94 |          98 |               chest | External_body_part_or_region |        1 |  0.9999529 |
+| 2 |        0 |             0 |          19 | TECHNIQUE IN DETAIL: |               Section_Header |           117 |         135 | portable ultrasound |                         Test |        1 |  0.9999838 |
+| 3 |        0 |            78 |          87 |           his mother |                       Gender |            94 |          98 |               chest | External_body_part_or_region |        1 |        1.0 |
+| 4 |        0 |            78 |          87 |           his mother |                       Gender |           117 |         135 | portable ultrasound |                         Test |        1 |  0.9999982 |
+| 5 |        0 |            94 |          98 |                chest | External_body_part_or_region |           117 |         135 | portable ultrasound |                         Test |        1 |        1.0 |
 ```
 
 {:.model-param}

diff --git a/docs/_posts/Cabir40/2023-04-03-summarizer_biomedical_pubmed_en.md b/docs/_posts/Cabir40/2023-04-03-summarizer_biomedical_pubmed_en.md
@@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java"
 
 ## Description
 
-This model is a modified version of Flan-T5 (LLM) based summarization model that is finetuned with biomedical datasets (Pubmed abstracts) by John Snow Labs.  It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
+This model is a modified version of LLM based summarization model that is finetuned with biomedical datasets (Pubmed abstracts) by John Snow Labs.  It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
 
 {:.btn-box}
 [Live Demo](https://demo.johnsnowlabs.com/healthcare/BIOMEDICAL_TEXT_SUMMARIZATION/){:.button.button-orange}

diff --git a/docs/_posts/Cabir40/2023-04-03-summarizer_clinical_questions_en.md b/docs/_posts/Cabir40/2023-04-03-summarizer_clinical_questions_en.md
@@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java"
 
 ## Description
 
-This model is a modified version of Flan-T5 (LLM) based summarization model that is finetuned with medical questions exchanged in clinical mediums (clinic, email, call center etc.) by John Snow Labs.  It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
+This model is a modified version of LLM based summarization model that is finetuned with medical questions exchanged in clinical mediums (clinic, email, call center etc.) by John Snow Labs.  It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
 
 {:.btn-box}
 [Live Demo](https://demo.johnsnowlabs.com/healthcare/MEDICAL_TEXT_SUMMARIZATION_QA/){:.button.button-orange}

diff --git a/docs/_posts/Cabir40/2023-08-16-summarizer_clinical_laymen_onnx_en.md b/docs/_posts/Cabir40/2023-08-16-summarizer_clinical_laymen_onnx_en.md
@@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java"
 
 ## Description
 
-This model is a modified version of Flan-T5 (LLM) based summarization model that is finetuned with custom dataset by John Snow Labs to avoid using clinical jargon on the summaries. It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
+This model is a modified version of LLM based summarization model that is finetuned with custom dataset by John Snow Labs to avoid using clinical jargon on the summaries. It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
 
 ## Predicted Entities
 

diff --git a/docs/_posts/Meryem1425/2023-05-31-summarizer_clinical_laymen_en.md b/docs/_posts/Meryem1425/2023-05-31-summarizer_clinical_laymen_en.md
@@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java"
 
 ## Description
 
-This model is a modified version of Flan-T5 (LLM) based summarization model that is finetuned with custom dataset by John Snow Labs to avoid using clinical jargon on the summaries.  It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
+This model is a modified version of LLM based summarization model that is finetuned with custom dataset by John Snow Labs to avoid using clinical jargon on the summaries.  It can generate summaries up to 512 tokens given an input text (max 1024 tokens).
 
 ## Predicted Entities
 
@@ -37,6 +37,7 @@ This model is a modified version of Flan-T5 (LLM) based summarization model that
 
 <div class="tabs-box" markdown="1">
 {% include programmingLanguageSelectScalaPythonNLU.html %}
+
 ```python
 document_assembler = DocumentAssembler()\
     .setInputCol("text")\

diff --git a/docs/_posts/ahmedlone127/2023-06-13-re_test_result_date_pipeline_en.md b/docs/_posts/ahmedlone127/2023-06-13-re_test_result_date_pipeline_en.md
@@ -63,11 +63,16 @@ nlu.load("en.relation.date_test_result.pipeline").predict("""He was advised ches
 ## Results
 
 ```bash
-| index | relations    | entity1      | chunk1              | entity2      |  chunk2 |
-|-------|--------------|--------------|---------------------|--------------|---------|
-| 0     | O            | TEST         | chest X-ray         | MEASUREMENTS |  93%    | 
-| 1     | O            | TEST         | CT scan             | MEASUREMENTS |  93%    |
-| 2     | is_result_of | TEST         | SpO2                | MEASUREMENTS |  93%    |
+|   | sentence | entity1_begin | entity1_end |      chunk1 | entity1 | entity2_begin | entity2_end |      chunk2 |     entity2 |      relation | confidence |
+|--:|---------:|--------------:|------------:|------------:|--------:|--------------:|------------:|------------:|------------:|--------------:|-----------:|
+| 0 |        0 |             0 |           1 |          He |  Gender |            15 |          25 | chest X-ray |        Test | is_finding_of |  0.9991597 |
+| 1 |        0 |             0 |           1 |          He |  Gender |            30 |          36 |     CT scan |        Test | is_finding_of |        1.0 |
+| 2 |        0 |            15 |          25 | chest X-ray |    Test |            30 |          36 |     CT scan |        Test | is_finding_of |        1.0 |
+| 3 |        0 |            30 |          36 |     CT scan |    Test |            53 |          55 |         his |      Gender | is_finding_of |        1.0 |
+| 4 |        0 |            30 |          36 |     CT scan |    Test |            57 |          60 |        SpO2 |        Test | is_finding_of |        1.0 |
+| 5 |        0 |            53 |          55 |         his |  Gender |            57 |          60 |        SpO2 |        Test |    is_date_of |    0.98956 |
+| 6 |        0 |            53 |          55 |         his |  Gender |            75 |          77 |         93% | Test_Result |    is_date_of |  0.9999974 |
+| 7 |        0 |            57 |          60 |        SpO2 |    Test |            75 |          77 |         93% | Test_Result |  is_result_of | 0.92868817 |
 ```
 
 {:.model-param}

diff --git a/docs/_posts/ahmedlone127/2023-06-22-icd10cm_resolver_pipeline_en.md b/docs/_posts/ahmedlone127/2023-06-22-icd10cm_resolver_pipeline_en.md
@@ -66,11 +66,11 @@ nlu.load("en.icd10cm_resolver.pipeline").predict("""A 28-year-old female with a
 ## Results
 
 ```bash
-|chunk                        |ner_chunk|icd10cm_code|
-+-----------------------------+---------+------------+
-|gestational diabetes mellitus|PROBLEM  |O24.919     |
-|anisakiasis                  |PROBLEM  |B81.0       |
-|fetal and neonatal hemorrhage|PROBLEM  |P545        |
+|   |                        chunks | entities | icd10cm_code |
+|--:|------------------------------:|---------:|-------------:|
+| 0 | gestational diabetes mellitus |  PROBLEM |      O24.919 |
+| 1 |                   anisakiasis |  PROBLEM |        B81.0 |
+| 2 | fetal and neonatal hemorrhage |  PROBLEM |         P549 |
 ```
 
 {:.model-param}

diff --git a/docs/_posts/mauro-nievoff/2022-12-01-oncology_therapy_pipeline_en.md b/docs/_posts/mauro-nievoff/2022-12-01-oncology_therapy_pipeline_en.md
@@ -33,6 +33,7 @@ This pipeline includes Named-Entity Recognition and Assertion Status models to e
 
 <div class="tabs-box" markdown="1">
 {% include programmingLanguageSelectScalaPythonNLU.html %}
+
 ```python
 from sparknlp.pretrained import PretrainedPipeline
 
@@ -112,11 +113,11 @@ nlu.load("en.oncology_therpay.pipeline").predict("""The patient underwent a mast
 
 ******************** assertion_oncology_treatment_binary_wip results ********************
 
-| chunk            | ner_label      | assertion       |
-|:-----------------|:---------------|:----------------|
-| mastectomy       | Cancer_Surgery | Present_Or_Past |
-| adriamycin       | Chemotherapy   | Present_Or_Past |
-| cyclophosphamide | Chemotherapy   | Present_Or_Past |
+|   |           chunks |       entities | assertion |
+|--:|-----------------:|---------------:|----------:|
+| 0 |       mastectomy | Cancer_Surgery |      Past |
+| 1 |       adriamycin |   Chemotherapy |   Present |
+| 2 | cyclophosphamide |   Chemotherapy |   Present |
 ```
 
 {:.model-param}

diff --git a/docs/_posts/murat-gunay/2020-09-01-posology_re.md b/docs/_posts/murat-gunay/2020-09-01-posology_re.md
@@ -75,7 +75,16 @@ reModel = RelationExtractionModel()\
     .setOutputCol("relations")\
     .setMaxSyntacticDistance(4)
 
-pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, words_embedder, pos_tagger, ner_tagger, ner_chunker, dependency_parser, reModel])
+pipeline = Pipeline(stages=[
+    document_assembler, 
+    sentence_detector, 
+    tokenizer, 
+    words_embedder, 
+    pos_tagger, 
+    ner_tagger, 
+    ner_chunker, 
+    dependency_parser, 
+    reModel])
 
 empty_data = spark.createDataFrame([[""]]).toDF("text")
 
@@ -84,7 +93,6 @@ model = pipeline.fit(empty_data)
 light_pipeline = LightPipeline(model)
 
 result = light_pipeline.fullAnnotate("The patient was prescribed 1 unit of Advil for 5 days after meals. The patient was also given 1 unit of Metformin daily. He was seen by the endocrinology service and she was discharged on 40 units of insulin glargine at night, 12 units of insulin lispro with meals, and metformin 1000 mg two times a day.")
-
 ```
 
 ```scala
@@ -130,15 +138,23 @@ val re_Model = RelationExtractionModel()
     .setOutputCol("relations")
     .setMaxSyntacticDistance(4)
 
-val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, words_embedder, pos_tagger, ner_tagger, ner_chunker, dependecy_parser, re_Model))
+val pipeline = new Pipeline().setStages(Array(
+    document_assembler, 
+    sentence_detector, 
+    tokenizer, 
+    words_embedder, 
+    pos_tagger, 
+    ner_tagger, 
+    ner_chunker, 
+    dependecy_parser, 
+    re_Model))
 
 val data = Seq("The patient was prescribed 1 unit of Advil for 5 days after meals. The patient was also given 1 unit of Metformin daily. He was seen by the endocrinology service and she was discharged on 40 units of insulin glargine at night, 12 units of insulin lispro with meals, and metformin 1000 mg two times a day.").toDS.toDF("text")
 
 val result = pipeline.fit(data).transform(data)
 ```
 </div>
 
-{:.h2_title}
 ## Results
 
 ```bash