Abstract The advent of Deep Learning (DL) has significantly propelled the field of diagnostic
radiology forward by enhancing image analysis and interpretation. The introduction of the …

Rapid technological advances have transformed medical education, particularly in
radiology, which depends on advanced imaging and visual data. Traditional electronic …

Large language models (LLMs) have shown potential in various applications, including
clinical practice. However, their accuracy and utility in providing treatment recommendations …

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their
diagnosis and treatment. The rapid advancement of artificial intelligence in imaging …

The use of large language models (LLMs) in clinical medicine is currently thriving. Effectively
transferring LLMs' pertinent theoretical knowledge from computer science to their application …

Electronic health records (EHRs) contain valuable patient data for health-related prediction
tasks, such as disease prediction. Traditional approaches rely on supervised learning …

BACKGROUND AND PURPOSE: MS is a chronic progressive, idiopathic, demyelinating
disorder whose diagnosis is contingent on the interpretation of MR imaging. New MR …

BACKGROUND AND PURPOSE: The review of clinical reports is an essential part of
monitoring disease progression. Synthesizing multiple imaging reports is also important for …

Introduction The healthcare sector invests significantly in communication skills training, but
not always with satisfactory results. Recently, generative Large Language Models, have …

To address challenges in the digital economy's landscape of digital intelligence, large
language models (LLMs) have been developed. Improvements in computational power and …