[Nature Reviews Bioengineering🔥] Application of Large Language Models in Medicine. A curated list of practical guide resources of Medical LLMs (Medical LLMs Tree, Tables, and Papers)

ClinVec: Unified Embeddings of Clinical Codes Enable Knowledge-Grounded AI in Medicine

[ NeurIPS 2022 ] Official Codebase for "ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography"

AI-powered chest X-ray pneumonia detection with 86% accuracy and 96.4% sensitivity, validated on an independent (cross-operator) cohort of 485 pediatric samples. Built with TensorFlow & FastAPI.

Systematic evaluation of hallucination risks in Large Language Models (GPT-4, Claude 3, Gemini Pro) for clinical proteomics and mass spectrometry interpretation. Production-ready detection framework with comprehensive benchmarks.

Ethnic bias analysis in medical imaging AI: Demonstrating that explainable-by-design models achieve 80% bias reduction across 5 ethnic groups (50k images)

An application to monitor clinical AI models

AI-powered thermal imaging system for early neonatal sepsis detection in NICUs. Non-invasive monitoring using deep learning to identify life-threatening infections before clinical symptoms appear. Collaboration with General University Hospital of Patras & Universitat Autònoma de Barcelona UAB.

Multimodal Agentic EHR Co-Pilot Stops The Expensive Crisis Hiding in Electronic Health Records

In-hospital cardiac mortality predictor trained on 15,757 real Indian patient records. Achieves AUC 0.977 using only routine blood tests & echo. Nurse-ready Streamlit web dashboard works on any phone in <3 sec. Discovered alcohol J-curve automatically. Ready for real ward deployment to save lives today.

Comprehensive literature review on hybrid AI systems combining temporal knowledge graphs, clinical constraints, and generative models for emergency department decision support

A clinical-grade malaria parasite detection system using YOLOv8 object detection with 99.14% mAP50 performance.

Production-grade clinical intelligence system speedrun: 95% accuracy, full explainability, zero pretrained models. Trained on class-weighted data, tested with real anxiety, deployed to impress recruiters.

This repository provides a compact RAG evaluation harness tailored for clinical + genomic use cases. It operates on de-identified synthetic notes and curated genomic snippets, measures retrieval quality and grounding/faithfulness, and produces JSONL/CSV/HTML reports.

Clinical + Genomic **RAG evaluation (pro)** with hybrid retrieval (BM25 + embeddings), stronger faithfulness, YAML configs, and HTML dashboards. Python **3.10+**.

A modern ASD screening support system combining XGBoost, SHAP explainability, and an Apple-Health inspired UI — fully deployed with PDF reporting and a complete end-to-end ML pipeline.

Clinical decision support system for chest X-ray analysis with explainable AI. Deep learning + Grad-CAM for transparent medical diagnosis. PyTorch | Medical Imaging | DICOM

[Project] Natural Language-Based Clinical Study Design Recommendation System

AI-powered platform detecting autism and developmental delays 6+ months earlier through smartphone assessments. Clinical-grade analysis for early intervention.

A multi-agent healthcare system that automates patient intake, triage, lab waiting, and clinician briefings using Google ADK.