Description
This pipeline, extracts age entities from clinical texts.
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("age_parser_pipeline", "en", "clinical/models")
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.
A 28 year old female with a history of gestational diabetes mellitus diagnosed 8 years ago.
3 years ago, he reported an episode of HTG-induced pancreatitis. 5 months old boy with repeated concussions.
A 45-year-old patient was admitted for routine examination.
The 72 years old man presented with chest pain."""
result = pipeline.transform(spark.createDataFrame([[sample_text]]).toDF("text"))
from johnsnowlabs import nlp, medical
pipeline = nlp.PretrainedPipeline("age_parser_pipeline", "en", "clinical/models")
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.
A 28 year old female with a history of gestational diabetes mellitus diagnosed 8 years ago.
3 years ago, he reported an episode of HTG-induced pancreatitis. 5 months old boy with repeated concussions.
A 45-year-old patient was admitted for routine examination.
The 72 years old man presented with chest pain."""
result = pipeline.transform(spark.createDataFrame([[sample_text]]).toDF("text"))
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = PretrainedPipeline("age_parser_pipeline", "en", "clinical/models")
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.
A 28 year old female with a history of gestational diabetes mellitus diagnosed 8 years ago.
3 years ago, he reported an episode of HTG-induced pancreatitis. 5 months old boy with repeated concussions.
A 45-year-old patient was admitted for routine examination.
The 72 years old man presented with chest pain."""
val result = pipeline.transform(spark.createDataFrame([[sample_text]]).toDF("text"))
Results
| chunk | begin | end | label |
|:-------------|--------:|------:|:--------|
| 60-year-old | 119 | 129 | AGE |
| 28 year old | 501 | 511 | AGE |
| 5 months old | 656 | 667 | AGE |
| 45-year-old | 702 | 712 | AGE |
| 72 years old | 764 | 775 | AGE |
Model Information
| Model Name: | age_parser_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 396.6 KB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- ContextualParserModel
- ChunkConverter