An NLP-powered Disease Prediction System that allows user to express his symptoms through speech, extracts symptom, and returns a predicted ailment. Used GPT-3 for extracting symptoms from user's speech and used Random Forest Classifier to train the machine learning model.
- Used Python's Speech Recognition with Google to accept user's speech as input for natural language processing and utilised OpenAI API to access GPT-3 in order t0 extract symptoms from the text input
- Used Python's scikit-learn library to train the model. The model was trained with a Random Forest algorithm.
- Used HTML, CSS and JavaScript to develop the front-end and used Python Flask web framework for the backend.
- Also used Flask to develop the API for the machine learning model
Clone and Fork this repository. Then navigate to the project directory. Then run pip install -r requirements.txt to install the required packages and dependencies. Then run python -m flask run to run the project with Flask.
- You can express your symptoms/problems by speech. Due to the efficient speech recognition library, your speech will be converted to text for symptom extraction.
- Symptoms are being extracted by the most capable Davinci model of GPT-3.
- The machine learning model is trained with Random Forest algorithm in the scikit-learn library.
- The UI of the project is also simple and effective.
This project is licensed under the MIT License. More information about this license can be found here.