In drug‐resistant epilepsy, magnetic resonance imaging (MRI) plays a central role in
detecting lesions as it offers unmatched spatial resolution and whole‐brain coverage. In …

Deep Learning (DL) holds great promise to improve patient outcomes by improving the
precision and speed of disease diagnosis and treatment recommendations. Given the …

The recent prevalence of publicly accessible, large medical imaging datasets has led to a
proliferation of artificial intelligence (AI) models for cardiovascular image classification and …

Background Due to conflicting findings in the literature, there are concerns about a lack of
objectivity in grading knee osteoarthritis (KOA) on radiographs. Purpose To examine how …

ABSTRACT BACKGROUND AND PURPOSE: Recently, AI tools have been deployed with
increasing speed in educational and clinical settings. However, the use of AI by trainees …

the researchers studying them. The LLMs may also modify our prompts and their outputs.
While this practice may serve as a guardrail against misuse, it can also have undesirable …

The study by Yu et al.[1] revealed that artificial intelligence (AI) has a heterogeneous effect
on individual radiologist performance improvement (treatment effect) in various tasks …

STE's ease of application and efficacy have been pivotal in advancing our understanding of
cardiac mechanics. It reignited interest in the intricate interplay between the spiraling …

A growing body of economic research explores the possible consequences of artificial
intelligence replacing or augmenting human labor, yet little is known about how AI might …

AMA: Physicians enthusiastic but cautious about health care AI [WWW Document], 2023..
American Medical Association. URL https://www. ama-assn. org/press-center/pressreleases …