ProCyon: A multimodal foundation model for protein phenotypes

BioContextAI Knowledgebase MCP server for biomedical agentic AI

The BioContextAI Registry for biomedical MCP servers

Cookiecutter template for MCP server development with FastMCP

Biomedical Artificial Intelligence

This repository contains a deep learning-based cancer type prediction system using a trained convolutional neural network (CNN). The model is deployed using Streamlit, allowing users to upload medical images and receive predictions with a probability distribution displayed in a pie chart.

Lightweight CNN with Attention for Heart Sound Classification

🩺 RAGnosis — An AI-powered clinical reasoning assistant that retrieves real diagnostic notes (from MIMIC-IV-Ext-DiReCT) and generates explainable medical insights using Mistral-7B & FAISS, wrapped in a clean Gradio UI. ⚡ GPU-ready, explainable, and open-source.

This repository contains a deep learning-based cancer type prediction system using a trained convolutional neural network (CNN). The model is deployed using Streamlit, allowing users to upload medical images and receive predictions with a probability distribution displayed in a pie chart.

Web-based semi-automated retinal fluid segmentation tool for OCT images. Combines traditional image processing with deep learning models (U-Net, MedSAM) to help medical professionals efficiently annotate and segment retinal fluid regions. Features interactive annotation tools, multiple segmentation algorithms, and user-friendly web interface.

Lab website

Deep learning system that interprets brain signals from EEG/fMRI to control devices, predict neurological disorders, and enable brain-computer interfaces.

Improving diagnostic confidence in histopathology through fine-tuned vision models and interpretable slide-level inference tools.

A custom Agentic Retrieval-Augmented Generation (RAG) model that is an expert in cell culture techniques and knowledge.