abdulazizhatem/Nabd-AI-Medical-Platform

AI for healthcare in low-resource settings. Nabd AI Medical Platform (منصة "نبض") AI for Healthcare in Low-Resource Settings This project is a submission for the Google - The Gemma 3n Impact Challenge. 🎯 The Problem In the heart of Yemen's healthcare sector, clinicians face immense daily challenges. Overwhelming patient loads leave little time for accurate, detailed documentation. Traditional paper-based records are prone to damage and loss, leading to the erosion of critical patient history. Furthermore, Yemen's rich dialectal diversity can create communication barriers between doctors and patients, while the absence of digital monitoring systems means that epidemic outbreaks are often detected too late. These challenges impact not only the efficiency of physicians but the quality of care for an entire population. ✨ Our Solution: The Nabd Platform From these challenges, Nabd (Pulse) was born. It is not just a tool, but an intelligent and reliable partner for the physician, specifically designed for the Yemeni context. Nabd is an integrated AI platform that listens to doctor-patient conversations and instantly generates structured medical reports, while also analyzing aggregated data to provide valuable public health insights. Nabd's core principle is being Offline-First. All processing happens locally on the doctor's device, ensuring 100% patient data privacy and guaranteeing functionality in any clinic, regardless of infrastructure quality. 🌟 Key Features 🌐 100% Offline Functionality: All audio and text processing is done on-device, ensuring unparalleled security, privacy, and reliability. 🇾🇪 Advanced Yemeni Dialect Support: Utilizes an innovative "Lexical Bridge" (a specialized Yemeni-to-Standard-Arabic dictionary) to interpret local dialects with high accuracy. 🩺 Structured Medical Reports: Automatically extracts vital information (chief complaint, history, assessment, plan) and generates a structured report ready for printing or archiving. 📈 Early Epidemic Warning System: By analyzing anonymize …