Description
This model, extracts date entities from clinical texts.
How to use
document_assembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
sentence_detector = SentenceDetectorDLModel.pretrained("sentence_detector_dl_healthcare","en","clinical/models")\
.setInputCols(["document"])\
.setOutputCol("sentence")
date_regex_matcher = RegexMatcherInternalModel.pretrained("date_matcher","en","clinical/models") \
.setInputCols(["sentence"]) \
.setOutputCol("date_parser")
parserPipeline = Pipeline(stages=[
document_assembler,
sentence_detector,
date_regex_matcher
])
sample_text = """Name : Hendrickson, Ora, Record date: 2093-01-13, # 719435.
Dr. John Green, ID: 1231511863, IP 203.120.223.13.
He is a 60-year-old male was admitted to the Day Hospital for cystectomy on 01/13/93.
Patient's VIN : 1HGBH41JXMN109286, VIN 4Y1SL65848Z411439, VIN 1HGCM82633A123456 - VIN JH4KA7560MC012345 - VIN 5YJSA1E14HF123456
SSN #333-44-6666, Driver's license no: A334455B, plate 34NLP34. Lic: 12345As. Cert: 12345As
Phone (302) 786-5227, 0295 Keats Street, San Francisco, E-MAIL: smith@gmail.com"""
data = spark.createDataFrame([[sample_text]]).toDF("text")
result = parserPipeline.fit(data).transform(data)
document_assembler = nlp.DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
sentence_detector = nlp.SentenceDetectorDLModel.pretrained("sentence_detector_dl_healthcare","en","clinical/models")\
.setInputCols(["document"])\
.setOutputCol("sentence")
date_regex_matcher = medical.RegexMatcherInternalModel.pretrained("date_matcher","en","clinical/models") \
.setInputCols(["sentence"]) \
.setOutputCol("date_parser")
parserPipeline = nlp.Pipeline(stages=[
document_assembler,
sentence_detector,
date_regex_matcher
])
sample_text = """Name : Hendrickson, Ora, Record date: 2093-01-13, # 719435.
Dr. John Green, ID: 1231511863, IP 203.120.223.13.
He is a 60-year-old male was admitted to the Day Hospital for cystectomy on 01/13/93.
Patient's VIN : 1HGBH41JXMN109286, VIN 4Y1SL65848Z411439, VIN 1HGCM82633A123456 - VIN JH4KA7560MC012345 - VIN 5YJSA1E14HF123456
SSN #333-44-6666, Driver's license no: A334455B, plate 34NLP34. Lic: 12345As. Cert: 12345As
Phone (302) 786-5227, 0295 Keats Street, San Francisco, E-MAIL: smith@gmail.com"""
data = spark.createDataFrame([[sample_text]]).toDF("text")
result = parserPipeline.fit(data).transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val sentence_detector = SentenceDetectorDLModel.pretrained("sentence_detector_dl_healthcare","en","clinical/models")
.setInputCols("document")
.setOutputCol("sentence")
val date_regex_matcher = RegexMatcherInternalModel.pretrained("date_matcher","en","clinical/models")
.setInputCols("sentence")
.setOutputCol("date_parser")
val parserPipeline = new Pipeline().setStages(Array(
document_assembler,
sentence_detector,
date_regex_matcher
))
val sample_text = """Name : Hendrickson, Ora, Record date: 2093-01-13, # 719435.
Dr. John Green, ID: 1231511863, IP 203.120.223.13.
He is a 60-year-old male was admitted to the Day Hospital for cystectomy on 01/13/93.
Patient's VIN : 1HGBH41JXMN109286, VIN 4Y1SL65848Z411439, VIN 1HGCM82633A123456 - VIN JH4KA7560MC012345 - VIN 5YJSA1E14HF123456
SSN #333-44-6666, Driver's license no: A334455B, plate 34NLP34. Lic: 12345As. Cert: 12345As
Phone (302) 786-5227, 0295 Keats Street, San Francisco, E-MAIL: smith@gmail.com"""
val data = Seq(sample_text).toDF("text")
val results = parserPipeline.fit(data).transform(data)
Results
+----------+-----+---+-----+
| chunk|begin|end|label|
+----------+-----+---+-----+
|2093-01-13| 38| 47| DATE|
| 01/13/93| 187|194| DATE|
|33-44-6666| 331|340| DATE|
+----------+-----+---+-----+
Model Information
| Model Name: | date_matcher |
| Compatibility: | Healthcare NLP 5.5.0+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [document] |
| Output Labels: | [entity_date] |
| Language: | en |
| Size: | 5.6 KB |