2022-10-29-icd10cm_mapper_en

docs/_posts/Ahmetemintek/2022-10-29-icd10cm_mapper_en.md

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+---
+layout: model
+title: Mapping Entities with Corresponding ICD-10-CM Codes
+author: John Snow Labs
+name: icd10cm_mapper
+date: 2022-10-29
+tags: [icd10cm, chunk_mapper, clinical, licensed, en]
+task: Chunk Mapping
+language: en
+edition: Spark NLP for Healthcare 4.2.1
+spark_version: 3.0
+supported: true
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This pretrained model maps entities with their corresponding ICD-10-CM codes.
+
+## Predicted Entities
+
+`icd10cm_code`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+[Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/26.Chunk_Mapping.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/icd10cm_mapper_en_4.2.1_3.0_1667082016627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol('text')\
+    .setOutputCol('document')
+
+sentence_detector = SentenceDetector()\
+    .setInputCols(["document"])\
+    .setOutputCol("sentence")
+
+tokenizer = Tokenizer()\
+    .setInputCols("sentence")\
+    .setOutputCol("token")
+
+word_embeddings = WordEmbeddingsModel\
+    .pretrained("embeddings_clinical", "en", "clinical/models")\
+    .setInputCols(["sentence", "token"])\
+    .setOutputCol("embeddings")
+
+ner_model = MedicalNerModel\
+    .pretrained("ner_clinical", "en", "clinical/models")\
+    .setInputCols(["sentence", "token", "embeddings"])\
+    .setOutputCol("ner")
+
+ner_converter = NerConverterInternal()\
+    .setInputCols("sentence", "token", "ner")\
+    .setOutputCol("ner_chunk")
+
+chunkerMapper = ChunkMapperModel\
+    .pretrained("icd10cm_mapper", "en", "clinical/models")\
+    .setInputCols(["ner_chunk"])\
+    .setOutputCol("mappings")\
+    .setRels(["icd10cm_code"])
+
+mapper_pipeline = Pipeline().setStages([
+    document_assembler,
+    sentence_detector,
+    tokenizer, 
+    word_embeddings,
+    ner_model, 
+    ner_converter, 
+    chunkerMapper])
+
+
+test_data = spark.createDataFrame([["A 35-year-old male with a history of primary leiomyosarcoma of neck, gestational diabetes mellitus diagnosed eight years prior to presentation and presented with a one-week history of polydipsia, poor appetite, and vomiting."]]).toDF("text")
+
+mapper_model = mapper_pipeline.fit(test_data)
+
+result= mapper_model.transform(test_data)
+```
+```scala
+val document_assembler = new DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+val sentence_detector = new SentenceDetector()\
+    .setInputCols(Array("document"))\
+    .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer()\
+    .setInputCols("sentence")\
+    .setOutputCol("token")
+
+val word_embeddings = WordEmbeddingsModel
+    .pretrained("embeddings_clinical", "en", "clinical/models")\
+    .setInputCols(Array("sentence", "token"))\
+    .setOutputCol("embeddings")
+
+val ner_model = MedicalNerModel
+    .pretrained("ner_clinical", "en", "clinical/models")\
+    .setInputCols(Array("sentence", "token", "embeddings"))\
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverterInternal()\
+    .setInputCols("sentence", "token", "ner")\
+    .setOutputCol("ner_chunk")
+
+val chunkerMapper = ChunkMapperModel
+    .pretrained("icd10cm_mapper", "en", "clinical/models")\
+    .setInputCols(Array("ner_chunk"))\
+    .setOutputCol("mappings")\
+    .setRels(Array("icd10cm_code")) 
+
+val mapper_pipeline = new Pipeline().setStages(Array(
+    document_assembler,
+    sentence_detector,
+    tokenizer, 
+    word_embeddings,
+    ner_model, 
+    ner_converter, 
+    chunkerMapper))
+
+
+val data = Seq("A 35-year-old male with a history of primary leiomyosarcoma of neck, gestational diabetes mellitus diagnosed eight years prior to presentation and presented with a one-week history of polydipsia, poor appetite, and vomiting.").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data) 
+```
+</div>
+
+## Results
+
+```bash
++------------------------------+-------+------------+
+|ner_chunk                     |entity |icd10cm_code|
++------------------------------+-------+------------+
+|primary leiomyosarcoma of neck|PROBLEM|C49.0       |
+|gestational diabetes mellitus |PROBLEM|O24.919     |
+|polydipsia                    |PROBLEM|R63.1       |
+|poor appetite                 |PROBLEM|R63.0       |
+|vomiting                      |PROBLEM|R11.10      |
++------------------------------+-------+------------+
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|icd10cm_mapper|
+|Compatibility:|Spark NLP for Healthcare 4.2.1+|
+|License:|Licensed|
+|Edition:|Official|
+|Input Labels:|[ner_chunk]|
+|Output Labels:|[mappings]|
+|Language:|en|
+|Size:|6.2 MB|