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Symps Disease Bert V3 C41

Developed by shanover
This is a BERT-based text classification model designed to identify related diseases based on user-described symptoms, supporting classification of 41 diseases.
Downloads 51
Release Time : 7/20/2023

Model Overview

This model is specifically designed for natural language chatbots, capable of analyzing user-input symptom texts in real-time and predicting possible diseases, suitable for dialogue systems in the healthcare domain.

Model Features

Multi-Disease Classification
Supports accurate classification of 41 common diseases, covering various medical conditions from the common cold to heart disease.
Real-time Symptom Analysis
Optimized for chatbot scenarios, capable of quickly processing natural language symptom descriptions input by users.
Medical Domain Optimization
Based on the BERT architecture, specifically trained and optimized for medical terminology and symptom descriptions.

Model Capabilities

Symptom Text Classification
Disease Probability Prediction
Natural Language Understanding

Use Cases

Healthcare
Preliminary Symptom Screening
After users describe their symptoms, the model can provide possible disease predictions as a preliminary reference for medical consultation.
Accurately identifies 41 common diseases
Health Chatbot
Integrated into dialogue systems to provide users with real-time symptom analysis and health advice.
Example includes recognition of typical cases such as heart disease and diabetes
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