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Cc 2 13 update #13513

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Feb 13, 2023
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Cc 2 13 update #13513

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7228983
RN updated
Feb 13, 2023
985c7db
RN updated
Feb 13, 2023
7f6db64
Merge branch 'master' into cc-2-13-update
Cabir40 Feb 13, 2023
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11 changes: 5 additions & 6 deletions docs/en/spark_nlp_healthcare_versions/licensed_release_notes.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -22,12 +22,12 @@ sidebar:
+ New text classification annotators (architectures) for training text classification models using SVM and Logistic Regression with sentence embeddings
+ One-liner clinical deidentification module
+ Certification_Training notebooks (written in johnsnowlabs library) moved to parent workshop folder
+ Different validation split per epoch in `MedicalNerApproach`
+ Core improvements and bug fixes
- New read_conll method for reading conll files as `Conll.readDataset` does but it returns pandas dataframe with document(task) ids.
- Updated documentation
- Allow using `FeatureAssembler` in pretrained pipelines.
- Fixed `RelationExtractionModel` running in LightPipeline
- Fixed validation and test sets spliting in `MedicalNerApproach`
- Fixed `get_conll_data` method issue
+ New and updated notebooks
- New [Clinical Deidentification Utility Module Notebook](https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/4.5.Clinical_Deidentification_Utility_Module.ipynb).
Expand All @@ -49,12 +49,11 @@ sidebar:
| model name | description | predicted entities |
|------------------------------------------------|-----------------------------------------------------------------------------------------------------|----------------------------------------|
| [ner_sdoh_wip](https://nlp.johnsnowlabs.com/2023/02/11/ner_sdoh_wip_en.html) | Extracts terminology related to Social Determinants of Health from various kinds of biomedical documents. | `Other_SDoH_Keywords` `Education` `Population_Group` `Quality_Of_Life` `Housing` `Substance_Frequency` `Smoking` `Eating_Disorder` `Obesity` `Healthcare_Institution` `Financial_Status` `Age` `Chidhood_Event` `Exercise` `Communicable_Disease` `Hypertension` `Other_Disease` `Violence_Or_Abuse` `Spiritual_Beliefs` `Employment` `Social_Exclusion` `Access_To_Care` `Marital_Status` `Diet` `Social_Support` `Disability` `Mental_Health` `Alcohol` `Insurance_Status` `Substance_Quantity` `Hyperlipidemia` `Family_Member` `Legal_Issues` `Race_Ethnicity` `Gender` `Geographic_Entity` `Sexual_Orientation` `Transportation` `Sexual_Activity` `Language` `Substance_Use`|
| [ner_sdoh_social_environment_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_social_environment_wip_en.html) | Extracts social environment terminologies related to Social Determinants of Health from various kinds of biomedical documents. | `Social_Support` `Chidhood_Event` `Social_Exclusion` ` Violence_Abuse_Legal` |
| [ner_sdoh_social_environment_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_social_environment_wip_en.html) | Extracts social environment terminologies related to Social Determinants of Health from various kinds of biomedical documents. | `Social_Support` `Chidhood_Event` `Social_Exclusion` `Violence_Abuse_Legal` |
| [ner_sdoh_demographics_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_demographics_wip_en.html) | Extracts demographic information related to Social Determinants of Health from various kinds of biomedical documents. | `Family_Member` `Age` `Gender` `Geographic_Entity` `Race_Ethnicity` `Language` `Spiritual_Beliefs` |
| [ner_sdoh_income_social_status_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_income_social_status_wip_en.html) | Extracts income and social status information related to Social Determinants of Health from various kinds of biomedical documents. | `Education` `Marital_Status` `Financial_Status` `Population_Group` `Employment` |



*Example*:

```python
Expand Down Expand Up @@ -397,8 +396,9 @@ shift_days=5)
+----------+------------+--------------------+---+----------------+
```

#### Different Validation Split Per Epoch In `MedicalNerApproach`


The validation splits in `MedicalNerApproach` used to be static and same for every epoch. Now we can control with behaviour with a new parameter called `setRandomValidationSplitPerEpoch(bool)` and allow users to set random validation splits per epoch.

#### Certification_Training Notebooks (Written In Johnsnowlabs Library) Moved to Parent Workshop Folder

Expand All @@ -410,11 +410,10 @@ shift_days=5)

#### Core Improvements and Bug Fixes

- New read_conll method for reading conll files as `Conll.readDataset` does but it returns pandas dataframe with document(task) ids.
- New read_conll method for reading conll files as `Conll.readDataset` does but it returns dataframe with document(task) ids.
- Updated documentation
- Allow using `FeatureAssembler` in pretrained pipelines.
- Fixed `RelationExtractionModel` running in LightPipeline
- Fixed validation and test sets spliting in `MedicalNerApproach`
- Fixed `get_conll_data` method issue


Expand Down
10 changes: 5 additions & 5 deletions docs/en/spark_nlp_healthcare_versions/release_notes_4_3_0.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -22,12 +22,12 @@ sidebar:
+ New text classification annotators (architectures) for training text classification models using SVM and Logistic Regression with sentence embeddings
+ One-liner clinical deidentification module
+ Certification_Training notebooks (written in johnsnowlabs library) moved to parent workshop folder
+ Different validation split per epoch in `MedicalNerApproach`
+ Core improvements and bug fixes
- New read_conll method for reading conll files as `Conll.readDataset` does but it returns pandas dataframe with document(task) ids.
- Updated documentation
- Allow using `FeatureAssembler` in pretrained pipelines.
- Fixed `RelationExtractionModel` running in LightPipeline
- Fixed validation and test sets spliting in `MedicalNerApproach`
- Fixed `get_conll_data` method issue
+ New and updated notebooks
- New [Clinical Deidentification Utility Module Notebook](https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/4.5.Clinical_Deidentification_Utility_Module.ipynb).
Expand All @@ -49,7 +49,7 @@ sidebar:
| model name | description | predicted entities |
|------------------------------------------------|-----------------------------------------------------------------------------------------------------|----------------------------------------|
| [ner_sdoh_wip](https://nlp.johnsnowlabs.com/2023/02/11/ner_sdoh_wip_en.html) | Extracts terminology related to Social Determinants of Health from various kinds of biomedical documents. | `Other_SDoH_Keywords` `Education` `Population_Group` `Quality_Of_Life` `Housing` `Substance_Frequency` `Smoking` `Eating_Disorder` `Obesity` `Healthcare_Institution` `Financial_Status` `Age` `Chidhood_Event` `Exercise` `Communicable_Disease` `Hypertension` `Other_Disease` `Violence_Or_Abuse` `Spiritual_Beliefs` `Employment` `Social_Exclusion` `Access_To_Care` `Marital_Status` `Diet` `Social_Support` `Disability` `Mental_Health` `Alcohol` `Insurance_Status` `Substance_Quantity` `Hyperlipidemia` `Family_Member` `Legal_Issues` `Race_Ethnicity` `Gender` `Geographic_Entity` `Sexual_Orientation` `Transportation` `Sexual_Activity` `Language` `Substance_Use`|
| [ner_sdoh_social_environment_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_social_environment_wip_en.html) | Extracts social environment terminologies related to Social Determinants of Health from various kinds of biomedical documents. | `Social_Support` `Chidhood_Event` `Social_Exclusion` ` Violence_Abuse_Legal` |
| [ner_sdoh_social_environment_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_social_environment_wip_en.html) | Extracts social environment terminologies related to Social Determinants of Health from various kinds of biomedical documents. | `Social_Support` `Chidhood_Event` `Social_Exclusion` `Violence_Abuse_Legal` |
| [ner_sdoh_demographics_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_demographics_wip_en.html) | Extracts demographic information related to Social Determinants of Health from various kinds of biomedical documents. | `Family_Member` `Age` `Gender` `Geographic_Entity` `Race_Ethnicity` `Language` `Spiritual_Beliefs` |
| [ner_sdoh_income_social_status_wip](https://nlp.johnsnowlabs.com/2023/02/10/ner_sdoh_income_social_status_wip_en.html) | Extracts income and social status information related to Social Determinants of Health from various kinds of biomedical documents. | `Education` `Marital_Status` `Financial_Status` `Population_Group` `Employment` |

Expand Down Expand Up @@ -397,8 +397,9 @@ shift_days=5)
+----------+------------+--------------------+---+----------------+
```

#### Different Validation Split Per Epoch In `MedicalNerApproach`


The validation splits in `MedicalNerApproach` used to be static and same for every epoch. Now we can control with behaviour with a new parameter called `setRandomValidationSplitPerEpoch(bool)` and allow users to set random validation splits per epoch.

#### Certification_Training Notebooks (Written In Johnsnowlabs Library) Moved to Parent Workshop Folder

Expand All @@ -410,11 +411,10 @@ shift_days=5)

#### Core Improvements and Bug Fixes

- New read_conll method for reading conll files as `Conll.readDataset` does but it returns pandas dataframe with document(task) ids.
- New read_conll method for reading conll files as `Conll.readDataset` does but it returns dataframe with document(task) ids.
- Updated documentation
- Allow using `FeatureAssembler` in pretrained pipelines.
- Fixed `RelationExtractionModel` running in LightPipeline
- Fixed validation and test sets spliting in `MedicalNerApproach`
- Fixed `get_conll_data` method issue


Expand Down