Extract clinical entities, assign assertion, and find relations.

Description

A pretrained pipeline with ner_clinical_events, assertion_dl and re_temporal_events_clinical trained with embeddings_healthcare_100d. It will extract clinical entities, assign assertion status and find temporal relationships between clinical entities.

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How to use

from sparknlp.pretrained import PretrainedPipeline

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]

annotations.keys()

Results

The output is a dictionary with the following keys: ‘sentences’, ‘clinical_ner_tags’, ‘clinical_ner_chunks_re’, ‘document’, ‘clinical_ner_chunks’, ‘assertion’, ‘clinical_relations’, ‘tokens’, ‘embeddings’, ‘pos_tags’, ‘dependencies’.

| #  | chunks                        | begin | end | entities      |
|----|-------------------------------|-------|-----|---------------|
| 0  | admitted                      | 7     | 14  | OCCURRENCE    |
| 1  | The John Hopkins Hospital     | 19    | 43  | CLINICAL_DEPT |
| 2  | 2 days ago                    | 45    | 54  | DATE          |
| 3  | gestational diabetes mellitus | 74    | 102 | PROBLEM       |
| 4  | diagnosed                     | 104   | 112 | OCCURRENCE    |
| 5  | denied                        | 119   | 124 | EVIDENTIAL    |
| 6  | pain                          | 126   | 129 | PROBLEM       |
| 7  | any headache                  | 135   | 146 | PROBLEM       |
| 8  | seen                          | 157   | 160 | OCCURRENCE    |
| 9  | the endocrinology service     | 165   | 189 | CLINICAL_DEPT |
| 10 | discharged                    | 203   | 212 | OCCURRENCE    |
| 11 | 03/02/2018                    | 217   | 226 | DATE          |
| 12 | insulin glargine              | 243   | 258 | TREATMENT     |
| 13 | insulin lispro                | 274   | 287 | TREATMENT     |
| 14 | metformin                     | 294   | 302 | TREATMENT     |
| 15 | two times a day               | 312   | 326 | FREQUENCY     |
| 16 | close follow-up               | 337   | 351 | OCCURRENCE    |
| 17 | endocrinology                 | 358   | 370 | CLINICAL_DEPT |
| 18 | discharge                     | 377   | 385 | OCCURRENCE    |

Model Information

Model Name: explain_clinical_doc_era
Type: pipeline
Compatibility: Spark NLP for Healthcare 2.6.0 +
License: Licensed
Edition: Official
Language: [en]

Included Models

  • ner_clinical_events
  • assertion_dl
  • re_temporal_events_clinical