Spark NLP for Healthcare Extract Relationships
Detect posology relations
Automatically identify relations between drugs, dosage, duration, frequency and strength using our pretrained clinical Relation Extraction (RE) model.
Detect temporal relations for clinical events
Automatically identify three types of relations between clinical events: After, Before and Overlap using our pretrained clinical Relation Extraction (RE) model.
Detect causality between symptoms and treatment
Automatically identify relations between symptoms and treatment using our pretrained clinical Relation Extraction (RE) model.
Detect relations between body parts and clinical entities
Use pre-trained relation extraction models to extract relations between body parts and clinical entities.
Detect how dates relate to clinical entities
Detect clinical entities such as problems, tests and treatments, and how they relate to specific dates.
Detect drugs interactions
Detect possible interactions between drugs using out-of-the-box Relation Extraction Spark NLP model.
Detect relations between chemicals and proteins
Automatically detect possible relationships between chemicals and proteins using a predefined Relation Extraction model.
Identify relations between scale items and measurements according to NIHSS
This demo shows how relations between scale items and their measurements can be identified according to NIHSS guidelines using a Spark NLP Healthcare RE model.
Identify Relations Between Drugs and Adversary Events
This demo shows how to detect relations between drugs and adverse reactions caused by them.
Extract relations between drugs and proteins
This model detects interactions between chemical compounds/drugs and genes/proteins.