[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

OpenEvidence MCP: open-source browser-session MCP server for human and AI-agent medical workflows

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

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

Comprehensive framework for curating and validating biomedical datasets for clinical AI applications

Full-stack clinical AI platform — multi-agent RAG over FHIR patient data with 20+ medical tools, hybrid vector search, and real-time streaming

AI surgical decision framework for spinal tumors (IMSCT, IDEM, MSCC) with skill-based reasoning, intraoperative monitoring logic, and DTI-assisted planning.

CodeSilver is an ambient AI prototype that translates clinical language into operational healthcare insights using synthetic data and public CMS rules, helping reduce documentation gaps without interrupting clinicians.

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.

Framework using UMAP-DBSCAN for unsupervised discovery of multi-modal Hidden Bias Subgroups (HBSs) in AI failure spaces. Implements a scalable Multi-Domain MMD Objective to mitigate latent Acquisition Bias and enhance robustness in clinical Ocular Disease Recognition (ODR).

Oloche's AI Oncologist is a diagnostic tool that detects breast cancer in its early stage using ML. The system analyzes measurements from breast mass characteristics to classify tumors as malignant or benign with high accuracy, providing medical professionals with a powerful decision-support tool

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.

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.