Disease Prediction

Welcome to the Disease Prediction repository! This project aims to leverage machine learning techniques to predict the likelihood of various diseases based on user input data. The goal is to provide an accessible tool for early diagnosis and preventive healthcare.

Introduction

The Disease Prediction project utilizes a machine learning model trained on medical data to predict the probability of a user having certain diseases. This can be particularly useful in areas with limited access to healthcare professionals, enabling users to get an early indication of potential health issues.

Features

User-friendly interface for inputting health data Predicts the likelihood of multiple diseases Provides a detailed report of the prediction results Scalable and easy to deploy

Technologies Used

• JavaScript: Main programming language
• React.js: Frontend library
• Node.js: Backend runtime environment
• Express.js: Web framework for the backend
• MongoDB: Database for storing user data
• TensorFlow.js: Machine learning library for training and inference

Usage

Open your web browser and go to http://localhost:3000.
Enter the required health data into the form.
Submit the form to get the prediction results.
Review the detailed report provided by the application.

Dataset

The dataset used for training the model is not included in the repository due to size and privacy constraints. However, you can use publicly available medical datasets or your own data to train the model. Ensure the data is preprocessed and cleaned before training.

Model Training

• To train the model: Ensure your dataset is in CSV format and located in the backend/data/ directory. Modify the trainModel.js script to load your dataset.

Built With

• express.js
• javascript
• mongodb
• node.js
• react.js
• tensorflow.js