en_biobert_ner_symptom

Fine-tuned BioBERT based NER model for detecting medical symptoms from clinical notes.

Model Description

The model was trained on a combined maccrobat and i2c2 dataset and is based on biobert. If you use this model kindly cite the paper below:

<b> <i> Uncovering Hidden Symptom Clusters in Patients with Acute Myeloid Leukemia using Natural Language Processing - Sena Chae, Jaewon Bae , Pratik Matira, Karen Dunn Lopez, Barbara Rakel </i> </b>

Model Usage

The model can be loaded using spacy after installing the model.

!pip install https://huggingface.co/pmaitra/en_biobert_ner_symptom/resolve/main/en_biobert_ner_symptom-any-py3-none-any.whl

A sample use-case is presented below:

import spacy
nlp = spacy.load("en_biobert_ner_symptom")

doc = nlp("He complained of dizziness and nausea during the Iowa trip.")

for ent in doc.ents:
  print(ent)

Accuracy