Abstract Background AI/ML CAD tools can potentially improve outcomes in the high-stakes,
high-volume model of trauma radiology. No prior sco** review has been undertaken to …

Deep learning has enabled breakthroughs in automated diagnosis from medical imaging,
with many successful applications in ophthalmology. However, standard medical image …

Open-source, publicly available neuroimaging datasets–whether from large-scale data
collection efforts or pooled from multiple smaller studies–offer unprecedented sample sizes …

Background Mitral annular plane systolic excursion (MAPSE) and left ventricular (LV) early
diastolic velocity (e') are key metrics of systolic and diastolic function, but not often measured …

Background: Artificial intelligence (AI) in echocardiography represents a transformative
advancement in cardiology, addressing longstanding challenges in cardiac diagnostics …

Abstract Objective and Impact Statement. In this work, we develop a universal anatomical
landmark detection model which learns once from multiple datasets corresponding to …

Purpose Integrating fleets of mobile service robots into the operating room wing (OR wing)
has the potential to help overcome staff shortages and reduce the amount of dull or …

Objectives Pustular psoriasis (PP) is one of the most severe and chronic skin conditions. Its
treatment is difficult, and measurements of its severity are highly dependent on clinicians' …

The cerebral cortex displays a bewildering diversity of shapes and sizes across and within
species. Despite this diversity, we present a universal multi-scale description of primate …

Methods One hundred and twenty cholecystectomy videos from a public dataset (Cholec80)
and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December …