The Cardiology Advisor

Deep Learning Model Can Predict Cardiopulmonary Disease in Retinal Images of Preterm Infants

A deep learning model using retinal images obtained during ROP screening may be used to predict diagnosis of BPD and PH.

AI model more accurately predicts cardiac event risk from PET scan data

Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic ...
News-Medical.Net

New model predicts redo surgery risk in adult congenital heart disease

Heart specialists at Mayo Clinic today presented new research at the 2026 Society of Thoracic Surgeons Annual Meeting that redo surgery for adults with congenital heart disease (CHD) remains high-risk ...

Study examines prediction of surgical risk in growing population of adults with congenital heart disease

Heart specialists at Mayo Clinic today presented new research at the 2026 Society of Thoracic Surgeons Annual Meeting that ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
IEEE

NefroAI: An Explainable and Real-Time Framework for Predicting Chronic Kidney Disease Using Diverse Machine Learning Models and Different Feature Selection Techniques

Abstract: Chronic Kidney Disease (CKD) is a serious health condition that progresses silently, often going undiagnosed until it reaches critical stages. Early detection is vital, but traditional ...
IEEE

Detection of Valvular Heart Diseases From PCG Signals Using Machine and Deep Learning Models: A Review

Abstract: Artificial intelligence (AI) predictions are widely used to address challenges in the heart health sector, such as providing clinical decision support. Early detection of valvular heart ...
The Lancet

Machine learning to classify the focus score and Sjögren's disease using digitalised salivary gland biopsies: a retrospective cohort study

bCentre for Translational Bioinformatics, William Harvey Research Institute, London, UK cExperimental Medicine and Rheumatology, William Harvey Research Institute, London, UK dSchool of Infection, ...
Frontiers

Hybrid intelligent systems for liver disease prediction: a demographic-aware machine learning framework

Background: Liver disease remains a major global health burden, often progressing undetected until advanced stages. Traditional diagnostic approaches, while accurate, are invasive, costly, and limited ...