{"repo":"MMansy19/cdss-xray-app","free":true,"listed":false,"github":"https://github.com/MMansy19/cdss-xray-app","clone":"git clone https://github.com/MMansy19/cdss-xray-app.git","description":"AI-powered Clinical Decision Support System (CDSS) for chest X-ray analysis, detecting pneumonia (89.9% accuracy) using CNN on Kaggle's Chest X-ray Dataset. Full-stack app with Next.js, Django, TensorFlow. Features drag-and-drop uploads, vitals input, and diagnostic reports.","language":"TypeScript","stars":24,"topics":["chest-xray-analysis","clinical-decision-support-system","convolutional-neural-networks","covid19-diagnosis","deep-learning","django","full-stack","healthcare-ai","kaggle","kaggle-dataset"],"license":null,"category":"machine-learning","readme_excerpt":"🩺 AI-Powered Chest X-Ray CDSS Live Demo Demo Video Kaggle Dataset A Clinical Decision Support System (CDSS) for analyzing chest X-ray images to detect pneumonia and aid COVID-19 diagnosis. Built with a Convolutional Neural Network (CNN) trained on the Kaggle Chest X-ray Pneumonia Dataset ( 5,000 images), achieving 89.9% accuracy. Features a full-stack architecture with Next.js, Django, TensorFlow, and PostgreSQL, supporting drag-and-drop uploads, patient vitals input, and detailed diagnostic reports. Includes demo and integrated BE modes for seamless UX. Developed as a course project at Cairo University, rivaling graduation project quality. This semi-graduation project demonstrates a clean architecture approach with three distinct service layers (Frontend, Backend, and AI Analysis) that work together to provide a comprehensive medical diagnostic tool. 📋 Table of Contents - Features - Tech Stack - Architecture - Getting Started - Clinical Workflow - UI & UX Highlights - Backend API Documentation - Deployment - Development Notes - License - Contributing - Author 📸 Features - 🖼️ X-ray Image Upload : Drag and drop interface for easy chest X-ray upload - 🤖 AI-powered Analysis : Advanced machine learning models for accurate diagnostic suggestions - 🔍 Heatmap Visualization : Visual highlighting of regions of interest in X-ray images - 📊 Detailed Results : Comprehensive diagnostic suggestions with confidence scores - 🔁 Rule-Based Fallback : Intelligent fallback mechanisms whe","default_branch":null,"files":null,"tree":[],"storefront":"/r/MMansy19","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/MMansy19/cdss-xray-app/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."}