Medical NER

Definition

Medical Named Entity Recognition (NER) is the process of identifying and classifying key medical terms such as diseases, symptoms, drugs, or procedures in clinical text.

Purpose

The purpose is to extract structured medical information from unstructured records, supporting healthcare analytics, research, and clinical decision-making.

Importance

  • Enables better use of electronic health records (EHRs).
  • Supports medical research and drug discovery.
  • Requires high precision due to clinical sensitivity.
  • Must follow data privacy and HIPAA/GDPR standards.

How It Works

  1. Collect medical documents or EHR data.
  2. Define entities of interest (diseases, treatments, drugs).
  3. Train NER models on annotated datasets.
  4. Apply models to extract entities in new records.
  5. Use results for clinical analytics or decision support.

Examples (Real World)

  • MIMIC-III dataset: annotated clinical notes for NER research.
  • IBM Watson Health: extracts medical entities from EHRs.
  • MetaMap (NIH): identifies biomedical concepts in text.

References / Further Reading

  • ISO/TS 22220: Health Informatics — Data Elements and Structures.
  • “Clinical Named Entity Recognition: A Review.” Journal of Biomedical Informatics.
  • MIMIC-III Clinical Database.