Elixer AI is a RAG-enabled LLM platform for secure, 100% accurate biomarker-based medical report analysis. It supports blood, urine, stool, sperm, and pap tests, with future-ready vision-LMM integration for imaging, plus EHR, hospital, and appointment support—built on React, Node, MongoDB, AWS, and Gemini AI.

This project uses OCR and machine learning to extract CBC values from reports and predict urgency levels. As of now, it supports image/pdf inputs, manual corrections, and SHAP explainability. Ideal for medical AI, healthcare OCR, and automated lab report analysis.

💻🔒 A local-first full-stack app to analyze medical PDFs with an AI model (Apollo2-2B), ensuring privacy & patient-friendly insights — no external APIs or cloud involved.

💻🔒 A local-first full-stack app to analyze medical PDFs with an AI model (Apollo2-2B), ensuring privacy & patient-friendly insights — no external APIs or cloud involved.

a powerful Python application designed to make medical test reports accessible to everyone. By uploading an image of a medical test report (e.g., blood tests, X-rays), users receive a clear, concise interpretation of their health status, including any abnormal results and actionable recommendations.

A comprehensive MedTech web application built with the MERN stack and integrated AI/ML for medical report analysis, symptom-based assessment, appointment booking, and WebRTC-based video consultations

forGrandma: Agentic AI for simplifying technical medical reports | Centrale Lyon UNBOXED Hackathon Submission sponsored by GE Healthcare & Mistral AI

Sehat Guftagu is an innovative AI-powered medical report analysis system that helps users understand their medical reports through interactive conversations.

A privacy-first OpenClaw skill that extracts useful medical data from manually redacted report images and saves minimal JSON locally.