Pipeline to find clinical events and find temporal relations (ERA)

Description

A pipeline with ner_clinical_events, assertion_dl and re_temporal_events_clinical. It will extract clinical entities, assign assertion status and find temporal relationships between clinical entities.

Live Demo Open in Colab Download

How to use

era_pipeline = PretrainedPipeline('explain_clinical_doc_era', 'en', 'clinical/models')

annotations =  era_pipeline.fullAnnotate("""She is admitted to The John Hopkins Hospital 2 days ago with a history of gestational diabetes mellitus diagnosed. She denied pain and any headache. She was seen by the endocrinology service and she was discharged on 03/02/2018 on 40 units of insulin glargine, 12 units of insulin lispro, and metformin 1000 mg two times a day. She had close follow-up with endocrinology post discharge. """)[0]

val era_pipeline = new PretrainedPipeline("explain_clinical_doc_era", "en", "clinical/models")

val result = era_pipeline.fullAnnotate("""She is admitted to The John Hopkins Hospital 2 days ago with a history of gestational diabetes mellitus diagnosed. She denied pain and any headache. She was seen by the endocrinology service and she was discharged on 03/02/2018 on 40 units of insulin glargine, 12 units of insulin lispro, and metformin 1000 mg two times a day. She had close follow-up with endocrinology post discharge. """)(0)

Results

|    | relation   | entity1       |   entity1_begin |   entity1_end | chunk1                    | entity2       |   entity2_begin |   entity2_end | chunk2                        |   confidence |
|---:|:-----------|:--------------|----------------:|--------------:|:--------------------------|:--------------|----------------:|--------------:|:------------------------------|-------------:|
|  0 | AFTER      | OCCURRENCE    |               7 |            14 | admitted                  | CLINICAL_DEPT |              19 |            43 | The John Hopkins Hospital     |     0.963836 |
|  1 | BEFORE     | OCCURRENCE    |               7 |            14 | admitted                  | DATE          |              45 |            54 | 2 days ago                    |     0.587098 |
|  2 | BEFORE     | OCCURRENCE    |               7 |            14 | admitted                  | PROBLEM       |              74 |           102 | gestational diabetes mellitus |     0.999991 |
|  3 | OVERLAP    | CLINICAL_DEPT |              19 |            43 | The John Hopkins Hospital | DATE          |              45 |            54 | 2 days ago                    |     0.996056 |
|  4 | BEFORE     | CLINICAL_DEPT |              19 |            43 | The John Hopkins Hospital | PROBLEM       |              74 |           102 | gestational diabetes mellitus |     0.995216 |
|  5 | OVERLAP    | DATE          |              45 |            54 | 2 days ago                | PROBLEM       |              74 |           102 | gestational diabetes mellitus |     0.996954 |
|  6 | BEFORE     | EVIDENTIAL    |             119 |           124 | denied                    | PROBLEM       |             126 |           129 | pain                          |     1        |
|  7 | BEFORE     | EVIDENTIAL    |             119 |           124 | denied                    | PROBLEM       |             135 |           146 | any headache                  |     1        |

Model Information

Model Name: explain_clinical_doc_era
Type: pipeline
Compatibility: Spark NLP for Healthcare 3.0.0+
License: Licensed
Edition: Official
Language: en