This model is designed for classifying medical intents from text using a specialized variant of ClinicalBERT. It was trained to understand and classify various medical intents based on patient dialogues and medical records. The model aims to enhance the understanding of medical phrases and intents in clinical settings.

The Clinical Intent Model was trained on a diverse dataset consisting of:

Training Data: A large multicenter dataset including a variety of medical dialogues and intents.

Pretraining Procedures Base Model: The model is initialized from the ClinicalBERT base model. Training Objective: The model is fine-tuned on the classification task of predicting medical intents. During fine-tuning, the model was exposed to a labeled dataset where phrases were categorized into predefined intents.