biomedical-ai

[ICML 2026] Autonomous AI agent for end-to-end spatial proteomics analysis, with SP-Bench for agentic multiplexed-imaging workflows.

ProCyon: A multimodal foundation model for protein phenotypes

BioContextAI Knowledgebase MCP server for biomedical agentic AI

A PMC ID in. Clean, loss-aware article JSON out. Parse PubMed Central and JATS XML for biomedical AI, RAG, search, and literature pipelines.

The BioContextAI Registry for biomedical MCP servers

MCP server for life-science knowledge graphs

Cookiecutter template for MCP server development with FastMCP

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.

🩺 AstraMed: A Clinical Risk Intelligence Platform. Powered by SOTA Ensemble ML & BioMistral-7B for predictive medical analytics and explainable risk scoring.

Biomedical Artificial Intelligence

Breast ultrasound image segmentation app using a U-Net with ResNet50V2 backbone, featuring an interactive Gradio demo and AI-based lesion detection.

AI-powered Semantic Literature Synthesis tool using RAG architecture for PubMed data.

A modular agentic AI software system demonstrating LLM reasoning, tool orchestration, and retrieval-augmented generation (RAG) using Python and the OpenAI Responses API.

Lab website

Open-source biomedical research agent with 60+ offline tools: variant interpretation. Use via web chat UI or MCP (DeepSeek-harness compatible).

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.

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

Production-ready system prompts and LLM templates for biomedical literature synthesis, VCF clinical variant interpretation, and Nextflow generation.

This project builds machine learning models to automatically detect and classify protein complexes in cryo-electron tomography (cryoET) images, enabling scalable analysis of cellular structures and supporting advanced biological and medical research.