Arnaout Lab

Research focus

NIH R01 · 2025

Toward efficient performance for deep learning on medical imaging

Project Summary / Abstract Objective — The goal of this renewal is to continue developing and optimizing novel deep learning (DL) and related methods to improve diagnosis and clinical decision-making for congenital heart disease (CHD). Nota- bly, this work includes a clinical translational evaluation of these methods in a population-wide imaging collec- tion spanning tens of thousands of patients and several clinical centers. Background — Despite clear and numerous benefits to prenatal detection of CHD and an ability for fetal ultrasound to detect over 90% of CHD in theory, in practice detection is closer to 50%. Literature suggests a key cause of this startling diagnosis gap is suboptimal…

From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.