LLM-based AI solution designed to augment clinical decision-making by analyzing doctors’ notes from patient examinations, identifying critical data points, and suggesting potential diagnoses. In effect, it provides a “second opinion” on the descriptions of a patient’s condition, combining text analysis with medical knowledge to increase diagnostic accuracy and consistency. By highlighting possible diagnoses and relevant clinical details, the tool supports both clinicians and patients in arriving at the right care strategy more quickly and confidently
- Clone repo
- Install Ollama
- Create virtual environment in backend
- Run pip install -r requirements in the backend folder
- Run npm install on frontend folder
- Set up your environment variables for the frontend and backend folders
- Run backend server using uvicorn
- Run frontend server using npm run dev
- Profit
Please do contact us if there are any issues with testing this. We do apologise for the ollama setup as thats the best way to test LLMs for free.
- Using OpenAI for processing
- Utilising RAG for better diagnostic accuracy/more specialised diagnosis
- Training an LLM for this project.