metadata

tags:
  - spacy
  - token-classification
  - named-entity-recognition
  - medical-ner
library_name: spacy
pipeline_tag: token-classification
language: en
license: mit

Medical NER Model - medical-ner-task3

This model is trained to recognize medical entities including treatments, chronic diseases, cancers, and allergies.

Model Details

Task: Named Entity Recognition
Framework: spaCy
Entity Types: TREATMENT, CHRONIC DISEASE, CANCER, ALLERGY, OTHER

Usage

import spacy
nlp = spacy.load("nitinyadav/continual_learning_ner_task3")
doc = nlp("Patient has been diagnosed with Type 2 Diabetes")
for ent in doc.ents:
    print(ent.text, ent.label_)

Entity Labels

TREATMENT: Medical treatments and procedures
CHRONIC DISEASE: Long-term medical conditions
CANCER: Cancer-related conditions
ALLERGY: Allergic conditions
OTHER: Other medical entities

Training Data

This model was trained on medical text data with annotated entities.