Patients with limited English proficiency face persistent barriers to equitable healthcare. Large language models (LLMs) may expand access to translation services; howeve[...]

Objective: This study synthesizes current evidence regarding the performance and clinical applications of artificial intelligence (AI)-assisted systems in radiolog[...]

Magnetic resonance fingerprinting (MRF) is a quantitative magnetic resonance imaging technique that generates tissue signals that vary based on chemical, physical, and bi[...]

Since the COVID-19 pandemic in 2020, telemedicine has become central to healthcare delivery, with physician use rising from 15.4% in 2019 to over 70% in 2024.1 Effective [...]

Background: Generative AI chatbots are now widely used, including for informal mental health support. Recently, psychiatrists have begun encountering patients wit[...]

Purpose: Language barriers and limited health literacy contribute to poor patient understanding and increased risk of adverse healthcare outcomes. Artificial intel[...]

The incorporation of artificial intelligence (AI) into clinical practice represents a pivotal shift in healthcare delivery. AI promises greater efficiency, diagnostic sup[...]

Artificial Intelligence (AI) has gained momentum in medicine, with radiology leading its adoption. Traditionally, radiologists maintain high diagnostic accuracy by integr[...]

Alzheimer’s disease (AD) is biologically heterogeneous, motivating a shift from symptom-based diagnosis toward biomarker-defined disease. The NIA-AA AT(N) framework forma[...]

Background: Multimodal large language models are increasingly discussed as potential adjuncts for medical image interpretation, yet the extent to which structured [...]