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

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.

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

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

Lab website

🩺 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 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.

Lightweight CNN with Attention for Heart Sound Classification

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.

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

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.

Overall Survival Prediction for Patients with Myeloid Leukemia

Exploring classical vs. quantum ML for Parkinson’s diagnosis using Qiskit, PennyLane, and IBM Quantum hardware. Alexandria Quantum Hackathon 2nd place project.

Brain Tumor Detection using a hybrid deep learning pipeline combining multi-model feature extraction, PCA-based dimensionality reduction, stacking ensemble classification, and YOLOv8 for accurate tumor localization in MRI scans.

Biomedical multimodal AI benchmark for pathology, genomics, clinical features, and survival prediction