AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

Unsupervised Feature Selection-Driven Active Learning for Semi-Supervised Automatic ECG Analysis

Abstract: Automatic analysis methods of electrocardiograms (ECGs) usually required large-scale annotated training data, but the annotation process is extremely time-consuming. While semi-supervised ...
IEEE

ECG, Respiration, fNIRS, and Eye Tracking for Stress and Mental Workload Monitoring in Human-Machine Interaction

Abstract: Advanced human-machine interaction (AHMI) is a key concept in human factors and ergonomics (HFE), focusing on how individuals interact with systems to perform tasks efficiently. As AHMI ...

AI-ECG: A New Market For A Century-Old Test

The 12-lead ECG hasn't changed in a century. The algorithms reading it have. Three CEOs and one educator on whether doctors should trust the model ...