Description
This pipeline can be used to detect clinical Admission Discharge in medical text, with a focus on admission entities.
Predicted Entities
ADMISSION_DISCHARGE
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_admission_discharge_benchmark_pipeline", "en", "clinical/models")
text = """
ADMISSION DATE :
12-6-93
DISCHARGE DATE :
12-9-93
IDENTIFYING DATA :
This 75 year old female was transferred from Iming Medical Center for angioplasty .
PRINCIPAL DIAGNOSIS :
Unstable angina .
ASSOCIATED DIAGNOSIS :
Hypertension .
PRINCIPAL PROCEDURE :
Right and circumflex angioplasty , cardiac catheterization on 12-6-93 .
HISTORY OF PRESENT ILLNESS :
This 75 year old woman was previously admitted here in November 1993 for chronic angina .
She had mild mitral regurgitation and a slightly diminished ejection fraction .
There was a 90% right coronary stenosis which was reduced to 30 with a balloon angioplasty .
There were three lesions in the circumflex , dilated successfully .
However , the low circumflex marginal vessel could not be crossed with the balloon .
"""
result = ner_pipeline.fullAnnotate(text)
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = nlp.PretrainedPipeline("ner_admission_discharge_benchmark_pipeline", "en", "clinical/models")
text = """
ADMISSION DATE :
12-6-93
DISCHARGE DATE :
12-9-93
IDENTIFYING DATA :
This 75 year old female was transferred from Iming Medical Center for angioplasty .
PRINCIPAL DIAGNOSIS :
Unstable angina .
ASSOCIATED DIAGNOSIS :
Hypertension .
PRINCIPAL PROCEDURE :
Right and circumflex angioplasty , cardiac catheterization on 12-6-93 .
HISTORY OF PRESENT ILLNESS :
This 75 year old woman was previously admitted here in November 1993 for chronic angina .
She had mild mitral regurgitation and a slightly diminished ejection fraction .
There was a 90% right coronary stenosis which was reduced to 30 with a balloon angioplasty .
There were three lesions in the circumflex , dilated successfully .
However , the low circumflex marginal vessel could not be crossed with the balloon .
"""
result = ner_pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_admission_discharge_benchmark_pipeline", "en", "clinical/models")
val text = """
ADMISSION DATE :
12-6-93
DISCHARGE DATE :
12-9-93
IDENTIFYING DATA :
This 75 year old female was transferred from Iming Medical Center for angioplasty .
PRINCIPAL DIAGNOSIS :
Unstable angina .
ASSOCIATED DIAGNOSIS :
Hypertension .
PRINCIPAL PROCEDURE :
Right and circumflex angioplasty , cardiac catheterization on 12-6-93 .
HISTORY OF PRESENT ILLNESS :
This 75 year old woman was previously admitted here in November 1993 for chronic angina .
She had mild mitral regurgitation and a slightly diminished ejection fraction .
There was a 90% right coronary stenosis which was reduced to 30 with a balloon angioplasty .
There were three lesions in the circumflex , dilated successfully .
However , the low circumflex marginal vessel could not be crossed with the balloon .
"""
val result = ner_pipeline.fullAnnotate(text)
Results
| | chunk | begin | end | ner_label |
|---:|:----------|--------:|------:|:--------------------|
| 0 | ADMISSION | 1 | 9 | ADMISSION_DISCHARGE |
| 1 | DISCHARGE | 26 | 34 | ADMISSION_DISCHARGE |
| 2 | admitted | 393 | 400 | ADMISSION_DISCHARGE |
Model Information
| Model Name: | ner_admission_discharge_benchmark_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.5.3+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetector
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- TextMatcherInternalModel
- ChunkMergeModel
- ChunkMergeModel
Benchmarking
label precision recall f1-score support
ADMISSION_DISCHARGE 0.983 0.986 0.984 799
O 1.000 1.000 1.000 81772
accuracy - - 1.000 82571
macro-avg 0.991 0.993 0.992 82571
weighted-avg 1.000 1.000 1.000 82571