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update md cards (#1126)
* update md cards * Update 2021-07-15-explain_clinical_doc_ade_en.md
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‎docs/_posts/C-K-Loan/2023-06-17-explain_clinical_doc_medication_en.md

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@@ -40,7 +40,7 @@ from sparknlp.pretrained import PretrainedPipeline
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pipeline = PretrainedPipeline("explain_clinical_doc_medication", "en", "clinical/models")
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text = '''The patient is a 30-year-old female with a long history of insulin dependent diabetes, type 2. She received a course of Bactrim for 14 days for UTI. She was prescribed 5000 units of Fragmin subcutaneously daily, and along with Lantus 40 units subcutaneously at bedtime.'''
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text = '''The patient is a 30-year-old female with an insulin dependent diabetes, type 2. She received a course of Bactrim for 14 days for UTI. She was prescribed 5000 units of Fragmin subcutaneously daily, and along with Lantus 40 units subcutaneously at bedtime.'''
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result = pipeline.fullAnnotate(text)
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```
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val pipeline = new PretrainedPipeline("explain_clinical_doc_medication", "en", "clinical/models")
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val text = "The patient is a 30-year-old female with a long history of insulin dependent diabetes, type 2. She received a course of Bactrim for 14 days for UTI. She was prescribed 5000 units of Fragmin subcutaneously daily, and along with Lantus 40 units subcutaneously at bedtime."
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val text = "The patient is a 30-year-old female with an insulin dependent diabetes, type 2. She received a course of Bactrim for 14 days for UTI. She was prescribed 5000 units of Fragmin subcutaneously daily, and along with Lantus 40 units subcutaneously at bedtime."
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val result = pipeline.fullAnnotate(text)
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```
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{:.nlu-block}
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```python
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import nlu
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nlu.load("en.explain_dco.clinical_medication.pipeline").predict("""The patient is a 30-year-old female with a long history of insulin dependent diabetes, type 2. She received a course of Bactrim for 14 days for UTI. She was prescribed 5000 units of Fragmin subcutaneously daily, and along with Lantus 40 units subcutaneously at bedtime.""")
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nlu.load("en.explain_dco.clinical_medication.pipeline").predict("""The patient is a 30-year-old female with an insulin dependent diabetes, type 2. She received a course of Bactrim for 14 days for UTI. She was prescribed 5000 units of Fragmin subcutaneously daily, and along with Lantus 40 units subcutaneously at bedtime.""")
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```
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</div>
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```bash
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# ner_chunk
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+----+----------------+------------+
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| | chunks | entities |
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|---:|:---------------|:-----------|
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| 0 | insulin | DRUG |
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| 1 | Bactrim | DRUG |
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| 2 | for 14 days | DURATION |
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| 3 | 5000 units | DOSAGE |
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| 4 | Fragmin | DRUG |
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| 5 | subcutaneously | ROUTE |
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| 6 | daily | FREQUENCY |
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| 7 | Lantus | DRUG |
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| 8 | 40 units | DOSAGE |
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| 9 | subcutaneously | ROUTE |
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| 10 | at bedtime | FREQUENCY |
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+----+----------------+------------+
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| | ner_chunk | begin | end | ner_label |
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|---:|---------------:|------:|----:|----------:|
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| 0 | insulin | 44 | 50 | DRUG |
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| 1 | Bactrim | 105 | 111 | DRUG |
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| 2 | for 14 days | 113 | 123 | DURATION |
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| 3 | 5000 units | 153 | 162 | DOSAGE |
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| 4 | Fragmin | 167 | 173 | DRUG |
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| 5 | subcutaneously | 176 | 189 | ROUTE |
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| 6 | daily | 191 | 195 | FREQUENCY |
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| 7 | Lantus | 213 | 218 | DRUG |
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| 8 | 40 units | 220 | 227 | DOSAGE |
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| 9 | subcutaneously | 229 | 242 | ROUTE |
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| 10 | at bedtime | 244 | 253 | FREQUENCY |
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# assertion
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+---+---------+----------+-----------+
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| | chunks | entities | assertion |
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|--:|--------:|---------:|----------:|
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| 0 | insulin | DRUG | Family |
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| 0 | insulin | DRUG | Present |
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| 1 | Bactrim | DRUG | Past |
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| 2 | Fragmin | DRUG | Planned |
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| 3 | Lantus | DRUG | Past |
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+---+---------+----------+-----------+
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# relation
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+----------------+-----------+------------+-----------+----------------+
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| relation | entity1 | chunk1 | entity2 | chunk2 |
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|:---------------|:----------|:-----------|:----------|:---------------|
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| DRUG-DURATION | DRUG | Bactrim | DURATION | for 14 days |
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| DOSAGE-DRUG | DOSAGE | 5000 units | DRUG | Fragmin |
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| DRUG-ROUTE | DRUG | Fragmin | ROUTE | subcutaneously |
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| DRUG-FREQUENCY | DRUG | Fragmin | FREQUENCY | daily |
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| DRUG-DOSAGE | DRUG | Lantus | DOSAGE | 40 units |
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| DRUG-ROUTE | DRUG | Lantus | ROUTE | subcutaneously |
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| DRUG-FREQUENCY | DRUG | Lantus | FREQUENCY | at bedtime |
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+----------------+-----------+------------+-----------+----------------+
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| | relation | entity1 | chunk1 | entity2 | chunk2 |
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|--:|---------------:|--------:|-----------:|----------:|---------------:|
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| 0 | DRUG-DURATION | DRUG | Bactrim | DURATION | for 14 days |
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| 1 | DOSAGE-DRUG | DOSAGE | 5000 units | DRUG | Fragmin |
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| 2 | DRUG-ROUTE | DRUG | Fragmin | ROUTE | subcutaneously |
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| 3 | DRUG-FREQUENCY | DRUG | Fragmin | FREQUENCY | daily |
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| 4 | DRUG-DOSAGE | DRUG | Lantus | DOSAGE | 40 units |
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| 5 | DRUG-ROUTE | DRUG | Lantus | ROUTE | subcutaneously |
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| 6 | DRUG-FREQUENCY | DRUG | Lantus | FREQUENCY | at bedtime |
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```
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{:.model-param}

‎docs/_posts/HashamUlHaq/2021-07-15-explain_clinical_doc_ade_en.md

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@@ -38,47 +38,44 @@ A pipeline for Adverse Drug Events (ADE) with `ner_ade_biobert`, `assertion_dl_b
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```python
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pipeline = PretrainedPipeline('explain_clinical_doc_ade', 'en', 'clinical/models')
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res = pipeline.fullAnnotate("""Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps""")
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res = pipeline.fullAnnotate("""Been taking Lipitor for 3 months, have experienced severe fatigue a lot!!!, have only experienced cramps so far, after Doctor moved me to voltaren 2 months ago.""")
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```
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```scala
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val era_pipeline = new PretrainedPipeline("explain_clinical_doc_ade", "en", "clinical/models")
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val result = era_pipeline.fullAnnotate("""Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps""")(0)
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val result = era_pipeline.fullAnnotate("""Been taking Lipitor for 3 months, have experienced severe fatigue a lot!!!, I have only experienced cramps so far, after Doctor moved me to voltaren 2 months ago.""")(0)
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```
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{:.nlu-block}
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```python
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import nlu
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nlu.load("en.explain_doc.clinical_ade").predict("""Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps""")
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nlu.load("en.explain_doc.clinical_ade").predict("""Been taking Lipitor for 3 months, have experienced severe fatigue a lot!!! , I have only experienced cramps so far, after Doctor moved me to voltaren 2 months ago.""")
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```
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</div>
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## Results
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```bash
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Assertion:
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Class: True
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NER_Assertion:
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| | chunk | entitiy | assertion |
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|----|-------------------------|------------|-------------|
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| 0 | Lipitor | DRUG | - |
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| 1 | severe fatigue | ADE | Conditional |
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| 2 | voltaren | DRUG | - |
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| 3 | cramps | ADE | Conditional |
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| | chunks | entities | assertion |
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|--:|---------------:|---------:|----------:|
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| 0 | Lipitor | DRUG | Past |
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| 1 | severe fatigue | ADE | Past |
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| 2 | cramps | ADE | Present |
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| 3 | voltaren | DRUG | Past |
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Relations:
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| | chunk1 | entitiy1 | chunk2 | entity2 | relation |
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|----|-------------------------------|------------|-------------|---------|----------|
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| 0 | severe fatigue | ADE | Lipitor | DRUG | 1 |
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| 1 | cramps | ADE | Lipitor | DRUG | 0 |
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| 2 | severe fatigue | ADE | voltaren | DRUG | 0 |
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| 3 | cramps | ADE | voltaren | DRUG | 1 |
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| | relation | entity1 | chunk1 | entity2 | chunk2 |
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|--:|---------:|--------:|--------:|--------:|---------------:|
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| 0 | 1 | DRUG | Lipitor | ADE | severe fatigue |
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| 1 | 0 | ADE | cramps | DRUG | voltaren |
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```
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