Spark NLP for Healthcare Recognize Clinical Entities
Detect signs and symptoms
Automatically identify Signs and Symptoms in clinical documents using two of our pretrained Spark NLP clinical models.
Detect diagnosis and procedures
Automatically identify diagnoses and procedures in clinical documents using the pretrained Spark NLP clinical model ner_clinical.
Detect drugs and prescriptions
Automatically identify Drug, Dosage, Duration, Form, Frequency, Route, and Strength details in clinical documents using three of our pretrained Spark NLP clinical models.
Adverse drug events tagger
Automatic pipeline that tags documents as containing or not containing adverse events description, then identifies those events.
Detect anatomical references
Automatically identify Anatomical System, Cell, Cellular Component, Anatomical Structure, Immaterial Anatomical Entity, Multi-tissue Structure, Organ, Organism Subdivision, Organism Substance, Pathological Formation in clinical documents using our pretrained Spark NLP model.
Detect clinical events
Automatically identify a variety of clinical events such as Problems, Tests, Treatments, Admissions or Discharges, in clinical documents using two of our pretrained Spark NLP models.
Detect lab results
Automatically identify Lab test names and Lab results from clinical documents using our pretrained Spark NLP model.
Detect biological concepts
Automatically identify biological entities such as Amino_acids, Anatomical systems, Cancer, Cells or Cellular components using our pertained Spark NLP model.
Detect clinical entities in text
Automatically detect more than 50 clinical entities using our NER deep learning model.
Detect risk factors
Automatically identify risk factors such as Coronary artery disease, Diabetes, Family history, Hyperlipidemia, Hypertension, Medications, Obesity, PHI, Smoking habits in clinical documents using our pretrained Spark NLP model.
Detect Clinical Entities in Radiology Reports
Automatically identify entities such as body parts, imaging tests, imaging results and diseases using a pre-trained Spark NLP model.
Identify diagnosis and symptoms assertion status
Automatically detect if a diagnosis or a symptom is present, absent, uncertain or associated to other persons (e.g. family members).
Detect Drug Chemicals (Bert For Token Classification)
This demo shows how drug chemicals can be extracted from medical texts using Spark NLP model which trained with BertForTokenClassifier.
Detect Wide Range of Clinical Entities (Bert For Token Classification)
This demo shows how clinical terminology can be extracted from medical texts using Spark NLP model which trained with BertForTokenClassifier.