RE Pipeline between Tests, Results, and Dates

Description

This pretrained pipeline is built on the top of re_test_result_date model.

Predicted Entities

Injury_or_Poisoning, Direction, Test, Route, Admission_Discharge, Death_Entity, Triglycerides, Oxygen_Therapy, Relationship_Status, Duration, Alcohol, Date, Drug, Hyperlipidemia, Respiration, Birth_Entity, VS_Finding, Age, Social_History_Header, Family_History_Header, Medical_Device, Labour_Delivery, BMI, Fetus_NewBorn, Temperature, Section_Header, Communicable_Disease, ImagingFindings, Psychological_Condition, Obesity, Sexually_Active_or_Sexual_Orientation, Modifier, Vaccine, Symptom, Pulse, Kidney_Disease, Oncological, EKG_Findings, Medical_History_Header, Cerebrovascular_Disease, Blood_Pressure, Diabetes, O2_Saturation, Heart_Disease, Employment, Frequency, Disease_Syndrome_Disorder, Pregnancy, RelativeDate, Procedure, Overweight, Race_Ethnicity, Hypertension, External_body_part_or_region, Imaging_Technique, Test_Result, Treatment, Substance, Clinical_Dept, LDL, Diet, Substance_Quantity, Allergen, Gender, RelativeTime, Total_Cholesterol, Internal_organ_or_component, Smoking, Vital_Signs_Header, Height, Form, Strength, Weight, Time, Dosage, HDL

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How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("re_test_result_date_pipeline", "en", "clinical/models")

pipeline.fullAnnotate("He was advised chest X-ray or CT scan after checking his SpO2 which was <= 93%")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("re_test_result_date_pipeline", "en", "clinical/models")

pipeline.fullAnnotate("He was advised chest X-ray or CT scan after checking his SpO2 which was <= 93%")
import nlu
nlu.load("en.relation.date_test_result.pipeline").predict("""He was advised chest X-ray or CT scan after checking his SpO2 which was <= 93%""")

Results

| index | relations    | entity1      | chunk1              | entity2      |  chunk2 |
|-------|--------------|--------------|---------------------|--------------|---------|
| 0     | O            | TEST         | chest X-ray         | MEASUREMENTS |  93%    | 
| 1     | O            | TEST         | CT scan             | MEASUREMENTS |  93%    |
| 2     | is_result_of | TEST         | SpO2                | MEASUREMENTS |  93%    |

Model Information

Model Name: re_test_result_date_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 1.7 GB

Included Models

  • DocumentAssembler
  • SentenceDetector
  • TokenizerModel
  • PerceptronModel
  • WordEmbeddingsModel
  • MedicalNerModel
  • NerConverter
  • DependencyParserModel
  • RelationExtractionModel