Advanced multi-agent Medical AI Assistant powered by LangGraph that delivers empathetic, doctor-like responses using a hybrid pipeline of LLM reasoning, RAG from medical PDFs, and intelligent fallback tools. Features Long-term memory with SQLite, dynamic tool routing, and state reasoning for reliable, context-aware consultation.

The Bencao RAG Medical Intelligent Assistant is a powerful AI-based medical knowledge question-answering system, designed to enhance user experience in knowledge-intensive tasks by integrating context awareness, internet access, knowledge graphs, and retrieval-augmented generation.

Production-ready AI medical chatbot for healthcare. IBM WatsonX, OpenAI, RAG, Llama 3, Mixtral. Medical interviewer, fine-tuning, Gradio. Python 3.9+.

AI-driven multi-disease risk assessment platform using Machine Learning, Explainable AI, and secure medical data analysis. Supports Diabetes, CKD, Parkinson’s and clinical insights for early detection and better healthcare decisions.

A doctor-assistive AI system that interprets medical knowledge and patient images simultaneously. It utilizes a Dual-Encoder architecture to cross-reference textbook theory with visual pathology, generating clinically grounded diagnoses.

🔍 Build a modular RAG system for multi-turn conversations, document ingestion, and vector search using FastAPI and OpenAI models.

TenaBot is a smart AI assistant that helps patients understand and follow medication instructions. It focuses on the Ethiopian context, translating drug information into local languages and providing guidance in a simple, user-friendly format.

🩺 Enhance medical diagnostics by integrating text and image analysis, bridging the gap for improved patient care with cutting-edge AI technology.

Multi-label chest X-ray classification across 14 diseases using DenseNet-121 vs EfficientNetB1 on NIH ChestX-ray14 — with Grad-CAM explainability | PyTorch | Medical AI