MedAI Digest

MedAI Digest

Daily AI medical research digest

Episodes

  1. 15H AGO

    AI-Powered Liver Transplant Selection: Multiagent Systems Show Promise for Objective Allocation

    An AI committee of specialized agents using GPT-4o accurately simulated liver transplant selection decisions, potentially reducing bias and inconsistency in this resource-limited allocation. Original paper: A multiagent large language model-based system to simulate the liver transplant selection committee: a retrospective cohort study. — The Lancet. Digital health. 10.1016/j.landig.2025.100966 📄 Read the article

  2. 15H AGO

    VarNet-T: Deep Learning Brings Precision to Tumor-Only Cancer Variant Detection

    VarNet-T, a deep learning framework, substantially improves identification of cancer mutations from tumor-only sequencing data, achieving up to 33% better accuracy than existing methods and enabling more reliable patient stratification for immunotherapy. Original paper: Improved tumor-only variant calling and mutation burden estimation with VarNet-T. — Nature communications. 10.1038/s41467-026-71705-4 📄 Read the article

  3. 15H AGO

    Your Lifetime Exposome Predicts Brain Aging

    A comprehensive analysis of 3,706 individuals reveals that cumulative lifetime exposures—your “exposome”—significantly predict structural brain preservation during aging, with cardiovascular health and lifestyle factors as key drivers. Original paper: Exposome-wide patterns predict brain health in aging. — Nature communications. 10.1038/s41467-026-71271-9 📄 Read the article

  4. 1D AGO

    When Machine Learning Models Cross Borders: Lessons from ELDER-ICU’s Global Validation

    A multicenter validation of ELDER-ICU, a machine learning model for predicting mortality in elderly ICU patients, reveals critical strategies for successfully deploying clinical AI across diverse international populations. Original paper: Multicenter validation and updating of the ELDER-ICU model for severity assessment in elderly critical illness. — NPJ digital medicine. 10.1038/s41746-026-02472-1 📄 Read the article

  5. 2D AGO

    Epicardial Fat Radiomics: Early Detection of Heart Failure Risk

    A radiomic signature of epicardial adipose tissue from routine cardiac CT identifies patients at high risk for heart failure, offering a scalable tool for early risk stratification. Original paper: Early Prediction of Heart Failure From Routine Cardiac CT Using Radiomic Phenotyping of Epicardial Fat. — Journal of the American College of Cardiology. 10.1016/j.jacc.2026.02.5116 📄 Read the article

  6. 2D AGO

    Head CT Scans Can Identify Hidden Heart Disease Risk in the ED

    Routine head CT scans performed in emergency departments can predict cardiovascular disease risk without additional cost, identifying high-risk patients who would otherwise be missed. Original paper: Opportunistic Cardiovascular Risk Assessment Using Routine Head CT in the Emergency Department. — Journal of the American College of Cardiology. 10.1016/j.jacc.2026.02.5095 📄 Read the article

  7. 2D AGO

    Lightweight AI Model for Breast Cancer Ultrasound Diagnosis Shows Clinical Promise

    Researchers developed USDist, a lightweight AI model that accurately diagnoses breast cancer from ultrasound videos and operates on portable devices in resource-limited settings. Original paper: Clinic-aligned Dual Distillation of Video and Image Foundation Models for Automated Breast Cancer US Diagnosis. — Radiology. Artificial intelligence. 10.1148/ryai.250600 📄 Read the article

  8. 2D AGO

    Predicting Breast Cancer Treatment Response with Integrated Imaging and Pathology AI

    A new explainable AI system combining MRI and tissue pathology predicts breast cancer response to neoadjuvant therapy before treatment begins, enabling personalized treatment strategies. Original paper: Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy. — Radiology. Artificial intelligence. 10.1148/ryai.250760 📄 Read the article

  9. 2D AGO

    Self-Powered Dental Implants Prevent Infection Through Chewing Force

    Autonomous piezoelectric dental implants harness natural chewing forces to generate protective antibacterial and anti-inflammatory responses, offering a novel strategy to prevent peri-implantitis without external intervention. Original paper: Occlusion-activated autonomous piezoelectric implants for adaptive prevention of peri-implantitis. — Nature Communications. 10.1038/s41467-026-71556-z 📄 Read the article

  10. 2D AGO

    Sleep EEG and Deep Learning Reveal a Powerful Brain Health Biomarker

    Researchers developed a deep learning model from overnight sleep EEG that predicts cognitive decline, disease risk, and mortality—offering a new clinical tool for brain health assessment. Original paper: Brain Health from Sleep EEG: A Multicohort, Deep Learning Biomarker for Cognition, Disease, and Mortality. — NEJM AI. 10.1056/aioa2500487 📄 Read the article

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