Heart — AI medical research

Cardiac Function AssessmentAI made heart MRI scans faster by using a single breath-hold method.This could help researchers measure heart function quicker and with less patient effort, improving study methods if validated further.HeartRead →
Radiotherapy Patient-Specific Quality AssuranceAI predicted radiotherapy dose quality for individual patients using anatomical features.This method could help researchers understand and measure dose delivery variations more quickly and transparently, improving radiotherapy plan checks if validated further.HeartRead →
Permanent Pacemaker Implantation After Transcatheter Aortic Valve ReplacementAI predicted pacemaker need after heart valve replacement with high accuracy.This could help researchers and doctors spot patients at risk for pacemaker need earlier, improving study design and patient monitoring if validated further.HeartRead →
Subclinical Leaflet ThrombosisAI models predicted hidden blood clots after valve implants in the heart.This could help researchers find which patients may have hidden clots early after valve implants. If validated further, it may guide better research on timing for imaging and treatments.HeartRead →
Atrial Fibrillation In Hypertrophic CardiomyopathyAI improved early prediction of atrial fibrillation in hypertrophic cardiomyopathy patients.This could help researchers better identify patients at risk earlier, improving measurement of factors linked to atrial fibrillation. If validated further, it may support focused study of early warning features.HeartRead →