{"id":24782189,"url":"https://github.com/thenishantraj/MediChateX","last_synced_at":"2025-10-12T05:31:31.618Z","repository":{"id":274743724,"uuid":"923925787","full_name":"thenishantraj/medicine-app","owner":"thenishantraj","description":"Medicine App\" is a cutting-edge, multi-platform healthcare solution that seamlessly connects patients, doctors, and machine learning! 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It consists of:\n- A **Flask backend** for handling API requests, integrating machine learning models, and managing patient data.\n- A **React.js frontend** for the web, providing a user-friendly interface to interact with the backend.\n- A **React Native mobile app** that allows users to access the platform from their mobile devices.\n\n## Table of Contents\n\n- [Features](#features)\n- [Tech Stack](#tech-stack)\n- [Backend](#backend)\n- [Frontend](#frontend)\n- [Mobile App](#mobile-app)\n- [Docker Setup](#docker-setup)\n- [How to Run](#how-to-run)\n- [License](#license)\n\n## Features\n\n- **Patient Management**: Add, update, and view patient records.\n- **Medicine Prediction**: Use machine learning to recommend medication based on the patient’s data.\n- **Multi-platform Support**: Accessible via a web app (React.js) and mobile app (React Native).\n- **User Authentication**: Login and Signup functionality for both web and mobile users.\n\n## Tech Stack\n\n- **Backend**: Flask, Python, SQLite, Machine Learning (e.g., Scikit-Learn)\n- **Frontend**: React.js, JavaScript, HTML, CSS\n- **Mobile App**: React Native, JavaScript\n- **Database**: SQLite\n- **Containerization**: Docker, Docker Compose\n\n## Backend\n\nThe backend is built using **Flask**, a lightweight Python framework. It includes an **API** for managing patient data, user authentication, and medicine predictions, powered by a machine learning model.\n\n### Setup\n\n1. Clone the repository:\n   ```bash\n   git clone \u003crepo_url\u003e\n   cd medicine-app/backend\n\n- **app.py**: This is the main Flask application file that handles API requests. It includes routes for user authentication, managing patient records, and recommending medicines using the trained ML model.\n  \n- **train_model.py**: This script trains the machine learning model using patient data and saves it as `medicine_model.pkl`. The model predicts recommended medicines based on user input.\n\n- **medicine_model.pkl**: The trained machine learning model. It is used by the backend to make predictions on the user's data and recommend relevant medicines.\n\n- **label_encoder.pkl**: The label encoder is used to convert categorical data (e.g., symptoms or conditions) into numerical data that the machine learning model can understand.\n\n- **patients.db**: An SQLite database that stores patient records, including personal details and medical history. This data is used by the backend to make more personalized recommendations.\n\n- **requirements.txt**: This file contains all the Python dependencies required for the backend, including Flask, Scikit-learn, and SQLite.\n\n- **README.md** (Backend): The documentation for the backend, explaining how to set up, run, and interact with the backend.\n\n## Frontend\n\nThe frontend is a **React.js** web application that provides a user-friendly interface for interacting with the backend API. It is designed to manage patient records, perform user authentication, and display the recommended medicines.\n\n### Directory Structure\n\n- **public/**: This folder contains static assets like `index.html`, logos, and other images required for the frontend.\n\n- **src/**: This folder contains the source code for the React application.\n\n  - **components/**: This subfolder contains reusable React components that make up different pages and sections of the application.\n    - **Login.js**: The component responsible for the login page where users can authenticate.\n    - **Signup.js**: The component responsible for the signup page where new users can register.\n    - **Navbar.js**: The component that defines the navigation bar used across the app.\n    - **Home.js**: The main page where users can input their symptoms to get medicine recommendations.\n    - **Results.js**: This page displays the recommended medicines based on the user's input.\n\n  - **App.js**: This is the root component that serves as the main container for the application.\n\n  - **App.css**: The CSS file responsible for styling the React app.\n\n  - **index.js**: The entry point of the React app, where it connects to the DOM and renders the app.\n\n- **package.json**: This file lists the Node.js dependencies required for the frontend, such as React and React Router.\n\n- **README.md** (Frontend): Documentation for setting up and running the React.js frontend.\n\n### Setup\n\n1. Navigate to the `frontend` directory:\n   ```bash\n   cd frontend\n\n\nThis markdown structure includes all relevant information, proper code formatting, and clear steps for setting up the project. It will display well in the `README.md` file when rendered on platforms like GitHub.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthenishantraj%2FMediChateX","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthenishantraj%2FMediChateX","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthenishantraj%2FMediChateX/lists"}