{"repo":"hallowshaw/PredictiX","free":true,"listed":false,"github":"https://github.com/hallowshaw/PredictiX","clone":"git clone https://github.com/hallowshaw/PredictiX.git","description":"PredictiX is a comprehensive multi-disease prediction system built using the MERN stack and integrated with machine learning models. It accurately predicts lung cancer, breast cancer, diabetes, and heart disease, providing a seamless user experience for health diagnostics.","language":"JavaScript","stars":16,"topics":["cnn","deep-learning","expressjs","inception-resnet-v2","javascript","machine-learning","mern-project","mern-stack","mongodb","nodejs"],"license":"MIT","category":"machine-learning","readme_excerpt":"PredictiX - Multi-Disease Prediction System PredictiX is a comprehensive multi-disease prediction platform designed to predict heart disease, diabetes, breast cancer, and lung cancer. Built using the MERN stack and integrated with machine learning models, PredictiX offers an intuitive interface for users to input data and receive accurate health predictions, enhancing the diagnostic experience. Table of Contents - Features - Tech Stack - Machine Learning Models - Usage - Frontend Design - File Structure - Screenshots - Future Enhancements - License Features - User Authentication: Secure sign-up and login functionality with protected routes using Context API. - Predictive Models: - Heart disease prediction using Logistic Regression. - Diabetes prediction using Support Vector Machine (SVM). - Breast cancer prediction using Convolutional Neural Network (CNN). - Lung cancer prediction using the InceptionResNet model. - Image Upload for Cancer Predictions: Users can upload medical images for breast and lung cancer detection. - Prescription Upload: Automatic form filling for heart disease and diabetes predictors using regex to scan user-uploaded prescriptions. - Custom PDF Reports: Generate a downloadable PDF report of prediction results. - Real-time Notifications: Integrated React Toasts for user-friendly notifications. - Single Server Deployment: Node.js Child Process is used to run all models, eliminating the need for a separate Flask server. Tech Stack - Frontend: React JS (wit","default_branch":null,"files":null,"tree":[],"storefront":"/r/hallowshaw","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/hallowshaw/PredictiX/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}