Description
This model classifies related to environment situation such as any indication of housing, homeless or no related passage. A discharge summary was classified as True for the SDOH Environment if there was any indication of housing, False if the patient was homeless and None if there was no related passage.
Predicted Entities
True, False, None
Live Demo Open in Colab Copy S3 URI
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
tokenizer = Tokenizer()\
.setInputCols("document")\
.setOutputCol("token")
sequenceClassifier = MedicalBertForSequenceClassification.pretrained("bert_sequence_classifier_sdoh_environment_status", "en", "clinical/models")\
.setInputCols(["document","token"])\
.setOutputCol("class")
pipeline = Pipeline(stages=[
document_assembler,
tokenizer,
sequenceClassifier
])
sample_texts = ["The patient is a 29-year-old female with a history of renal transplant in 2097, who had worsening renal failure for the past several months. Her chief complaints were hypotension and seizure. months prior to admission and had been more hypertensive recently, requiring blood pressure medications. She was noted to have worsening renal function secondary to recent preeclampsia and her blood pressure control was thought to be secondary to renal failure.",
"Mr Known lastname 19017 is a 66 year-old man with a PMHx of stage 4 COPD (FEV1 0.65L;FEV1/FVC 37% predicted in 4-14) on 4L home o2 with numerous hospitalizations for COPD exacerbations and intubation, hypertension, coronary artery disease, GERD who presents with SOB and CP. He is admitted to the ICU for management of dyspnea and hypotension.",
"He was deemed Child's B in 2156-5-17 with ongoing ethanol abuse, admitted to Intensive Care Unit due to acute decompensation of chronic liver disease due to alcoholic hepatitis and Escherichia coli sepsis. after being hit in the head with the a bottle and dropping to the floor in the apartment. They had Trauma work him up including a head computerized tomography scan which was negative. He had abdominal pain for approximately one month with increasing abdominal girth, was noted to be febrile to 100 degrees on presentation and was tachycardiac 130, stable blood pressures. He was noted to have distended abdomen with diffuse tenderness computerized tomography scan of the abdomen which showed ascites and large nodule of the liver, splenomegaly, paraesophageal varices and loops of thickened bowel."]
data = spark.createDataFrame(sample_texts, StringType()).toDF("text")
result = pipeline.fit(data).transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols("document")
.setOutputCol("token")
val sequenceClassifier = MedicalBertForSequenceClassification.pretrained("bert_sequence_classifier_sdoh_environment_status", "en", "clinical/models")
.setInputCols(Array("document","token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(document_assembler,
tokenizer,
sequenceClassifier))
val data = Seq("The patient is a 29-year-old female with a history of renal transplant in 2097, who had worsening renal failure for the past several months. Her chief complaints were hypotension and seizure. months prior to admission and had been more hypertensive recently, requiring blood pressure medications. She was noted to have worsening renal function secondary to recent preeclampsia and her blood pressure control was thought to be secondary to renal failure.")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.classify.bert_sequence.sdoh.environment_status").predict("""He was deemed Child's B in 2156-5-17 with ongoing ethanol abuse, admitted to Intensive Care Unit due to acute decompensation of chronic liver disease due to alcoholic hepatitis and Escherichia coli sepsis. after being hit in the head with the a bottle and dropping to the floor in the apartment. They had Trauma work him up including a head computerized tomography scan which was negative. He had abdominal pain for approximately one month with increasing abdominal girth, was noted to be febrile to 100 degrees on presentation and was tachycardiac 130, stable blood pressures. He was noted to have distended abdomen with diffuse tenderness computerized tomography scan of the abdomen which showed ascites and large nodule of the liver, splenomegaly, paraesophageal varices and loops of thickened bowel.""")
Results
+----------------------------------------------------------------------------------------------------+-------+
| text| result|
+----------------------------------------------------------------------------------------------------+-------+
|The patient is a 29-year-old female with a history of renal transplant in 2097, who had worsening...| [None]|
|Mr Known lastname 19017 is a 66 year-old man with a PMHx of stage 4 COPD (FEV1 0.65L;FEV1/FVC 37%...|[False]|
|He was deemed Child's B in 2156-5-17 with ongoing ethanol abuse, admitted to Intensive Care Unit ...| [True]|
+----------------------------------------------------------------------------------------------------+-------+
Model Information
| Model Name: | bert_sequence_classifier_sdoh_environment_status |
| Compatibility: | Healthcare NLP 4.2.2+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [class] |
| Language: | en |
| Size: | 410.9 MB |
| Case sensitive: | true |
| Max sentence length: | 512 |
Benchmarking
label precision recall f1-score support
None 0.89 0.78 0.83 277
False 0.86 0.93 0.90 419
True 0.67 1.00 0.80 6
accuracy - - 0.87 702
macro-avg 0.81 0.90 0.84 702
weighted-avg 0.87 0.87 0.87 702