Sentence Entity Resolver for UMLS CUI Codes

Description

Map clinical entities to UMLS CUI codes.

Predicted Entities

This model returns CUI (concept unique identifier) codes for 200K concepts from clinical findings. https://www.nlm.nih.gov/research/umls/index.html

Live Demo Open in Colab Download

How to use

...
chunk2doc = Chunk2Doc().setInputCols("ner_chunk").setOutputCol("ner_chunk_doc")

sbert_embedder = BertSentenceEmbeddings\
.pretrained("sbiobert_base_cased_mli",'en','clinical/models')\
.setInputCols(["ner_chunk_doc"])\
.setOutputCol("sbert_embeddings")

resolver = SentenceEntityResolverModel
.pretrained("sbiobertresolve_umls_findings","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

pipeline = Pipeline(stages = [documentAssembler, sentenceDetector, tokenizer, stopwords, word_embeddings, clinical_ner, ner_converter, chunk2doc, sbert_embedder, resolver])

data = spark.createDataFrame([["""A 28-year-old female with a history of gestational diabetes mellitus diagnosed eight years prior to presentation and subsequent type two diabetes mellitus (T2DM), one prior episode of HTG-induced pancreatitis three years prior to presentation, associated with an acute hepatitis, and obesity with a body mass index (BMI) of 33.5 kg/m2, presented with a one-week history of polyuria, polydipsia, poor appetite, and vomiting."""]]).toDF("text")

results = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.resolve.umls.findings").predict("""A 28-year-old female with a history of gestational diabetes mellitus diagnosed eight years prior to presentation and subsequent type two diabetes mellitus (T2DM), one prior episode of HTG-induced pancreatitis three years prior to presentation, associated with an acute hepatitis, and obesity with a body mass index (BMI) of 33.5 kg/m2, presented with a one-week history of polyuria, polydipsia, poor appetite, and vomiting.""")

Results

|    | ner_chunk                             | cui_code   |
|---:|:--------------------------------------|:-----------|
|  0 | gestational diabetes mellitus         | C2183115   |
|  1 | subsequent type two diabetes mellitus | C3532488   |
|  2 | T2DM                                  | C3280267   |
|  3 | HTG-induced pancreatitis              | C4554179   |
|  4 | an acute hepatitis                    | C4750596   |
|  5 | obesity                               | C1963185   |
|  6 | a body mass index                     | C0578022   |
|  7 | polyuria                              | C3278312   |
|  8 | polydipsia                            | C3278316   |
|  9 | poor appetite                         | C0541799   |
| 10 | vomiting                              | C0042963   |

Model Information

Model Name: sbiobertresolve_umls_findings
Compatibility: Spark NLP for Healthcare 3.0.2+
License: Licensed
Edition: Official
Input Labels: [sentence_embeddings]
Output Labels: [umls_code]
Language: en

Data Source

https://www.nlm.nih.gov/research/umls/index.html