Pipeline to Detect Temporal Relations for Clinical Events

Description

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

Predicted Entities

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

Live Demo Open in Colab Download Copy S3 URI

How to use

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


pipeline.annotate("The patient is a 56-year-old right-handed female with longstanding intermittent right low back pain, who was involved in a motor vehicle accident in September of 2005. At that time, she did not notice any specific injury, but five days later, she started getting abnormal right low back pain.")

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


pipeline.annotate("The patient is a 56-year-old right-handed female with longstanding intermittent right low back pain, who was involved in a motor vehicle accident in September of 2005. At that time, she did not notice any specific injury, but five days later, she started getting abnormal right low back pain.")

import nlu
nlu.load("en.relation.temporal_event_clinical.pipeline").predict("""The patient is a 56-year-old right-handed female with longstanding intermittent right low back pain, who was involved in a motor vehicle accident in September of 2005. At that time, she did not notice any specific injury, but five days later, she started getting abnormal right low back pain.""")

Results

+----+------------+------------+-----------------+---------------+--------------------------+-----------+-----------------+---------------+---------------------+--------------+
|    | relation   | entity1    |   entity1_begin |   entity1_end | chunk1                   | entity2   |   entity2_begin |   entity2_end | chunk2              |   confidence |
+====+============+============+=================+===============+==========================+===========+=================+===============+=====================+==============+
|  0 | OVERLAP    | OCCURRENCE |             121 |           144 | a motor vehicle accident | DATE      |             149 |           165 | September of 2005   |     0.999975 |
+----+------------+------------+-----------------+---------------+--------------------------+-----------+-----------------+---------------+---------------------+--------------+
|  1 | OVERLAP    | DATE       |             171 |           179 | that time                | PROBLEM   |             201 |           219 | any specific injury |     0.956654 |
+----+------------+------------+-----------------+---------------+--------------------------+-----------+-----------------+---------------+---------------------+--------------+

Model Information

Included Models

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