{"id":17703340,"url":"https://github.com/ayu-hack/disease-prediction","last_synced_at":"2026-03-01T03:02:13.432Z","repository":{"id":242068553,"uuid":"808603130","full_name":"Ayu-hack/Disease-Prediction","owner":"Ayu-hack","description":"The Disease Prediction project uses machine learning to predict disease likelihood based on user input. It features a user-friendly interface, detailed prediction reports, and scalable architecture. 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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.\n\n# Table of Contents\n\n* Introduction\n\n* Features\n\n* Technologies Used\n\n* Installation\n\n* Usage\n\n* Dataset\n\n* Model Training\n\n* Contributing\n\n* License\n\n* Contact\n\n# Introduction\n\nThe 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.\n\n# Features\n\nUser-friendly interface for inputting health data\nPredicts the likelihood of multiple diseases\nProvides a detailed report of the prediction results\nScalable and easy to deploy\n\n# Technologies Used\n\n* **JavaScript**: Main programming language\n* **React.js**: Frontend library\n* **Node.js**: Backend runtime environment\n* **Express.js**: Web framework for the backend\n* **MongoDB**: Database for storing user data\n* **TensorFlow.js**: Machine learning library for training and inference\n\n# Installation\n\n**To get a local copy up and running, follow these steps**:\n\n**Clone the repository**:\n\n```\ngit clone https://github.com/Ayu-hack/Disease-Prediction.git \ncd Disease-Prediction\n```\n\n**Install the required packages for both the backend and frontend**:\n```\ncd backend\nnpm install\ncd ../frontend\nnpm install\n```\n**Set up environment variables**:\nCreate a .env file in the backend directory and add the following:\n```\nenv\nMONGODB_URI= //your_mongodb_connection_string\nPORT=5000\n```\n**Start the frontend server**:\n```\ncd frontend\nnpm run dev\n```\n**Start the backend server:**\n```\ncd backend\nnpm start\n```\n# Usage\n```\nOpen your web browser and go to http://localhost:3000.\nEnter the required health data into the form.\nSubmit the form to get the prediction results.\nReview the detailed report provided by the application.\n```\n# Dataset\n\nThe 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.\n\n# Model Training\n\n* **To train the model**:\n```\nEnsure your dataset is in CSV format and located in the backend/data/ directory.\nModify the trainModel.js script to load your dataset.\n```\n* **Run the training script**:\n```\ncd backend\nnode trainModel.js\nThe trained model will be saved to the backend/models/ directory.\n```\n# Contributing\n\n**Contributions are welcome! Please follow these steps to contribute**:\n\n* Fork the repository.\n* Create a new branch (git checkout -b feature/YourFeature).\n* Commit your changes (git commit -m 'Add some feature').\n* Push to the branch (git push origin feature/YourFeature).\n* Open a pull request.\n\n# Contact\n\n**For questions or suggestions, please contact:**\n\nName: Ayu-hack\nEmail: ayushtiwari2100@gmail.com\n\n**Thank you for visiting our repository! We hope our project aids in advancing healthcare accessibility and early disease detection.**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fayu-hack%2Fdisease-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fayu-hack%2Fdisease-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fayu-hack%2Fdisease-prediction/lists"}