Latest AI and machine learning research in surveys for healthcare professionals.
OBJECTIVES: To 1) improve pharmacy students' perceived confidence in communication skills and 2) identify perceptions of counseling a text-based AI-simulated patient using ChatGPT 4o. METHODS: This study involved first-year pharmacy students in a required communications course at the University of Georgia. Four AI-simulated patients with unique characteristics and medication-related problems were ...
INTRODUCTION: Oral capsules for gastric submucosal delivery represent a fundamentally new route of administration for biologics, which are currently limited to injection. Involving patients and members of the public to understand their perspectives on this novel pharmaceutical form, distinct from both injections and traditional oral tablets, is essential for the clinical development, regulatory ap...
BACKGROUND: Clinical rating scales for Parkinson's disease (PD) have limitations in the accurate assessment of disease severity, which may obscure tre...
OBJECTIVE: To systematically evaluate the diagnostic accuracy and methodological quality of machine learning (ML) prediction models for pregnancy outc...
BACKGROUND: Large language models are increasingly used in health professions education; however, the role of prompt design in shaping their outputs r...
Urine is an attractive source of cancer biomarkers because it can be collected non-invasively and repeatedly, yet high diagnostic accuracy in early st...
OBJECTIVE: To develop and internally validate an interpretable machine-learning model using routine precollection variables to predict mononuclear cel...
BACKGROUND: AI is increasingly discussed and deployed in health care, yet safe and effective implementation depends on the preparedness, trust, and tr...
BACKGROUND: Infant feeding practices, including breastfeeding, are known to benefit maternal and child health outcomes. Therefore, parent access to ev...
As large language models (LLMs) are increasingly integrated into decision-making systems (e.g., autonomous vehicles and medical devices), understandin...
Artificial intelligence (AI) is increasingly permeating healthcare, from serving as a physician assistant to powering consumer applications. The opaci...
Using large language models (LLMs) with persona-based prompt engineering, this study simulates realistic insufficient effort responding (IER) data und...
PURPOSE: To present a novel, nonlinear subspace modeling and joint k-q-space reconstruction technique for high-resolution, multi-band, multi-shell dif...
BACKGROUND: In this methodological Brief Report, we describe a multi-institutional survey authentication challenge encountered during pilot deployment...
BACKGROUND: Thirty-day unplanned readmission following coronary artery bypass grafting (CABG) affects 10%-20% of patients and is a key quality indicat...
BACKGROUND: AI is increasingly embedded in health care systems; yet, validated instruments for assessing AI literacy among health care workers remain ...
Artificial intelligence (AI) has rapidly advanced in breast cancer imaging, demonstrating high diagnostic and predictive performance across imaging mo...
Arterial wall shear stress (WSS) plays an important role in atherosclerosis, but its assessment is often limited to small, retrospective studies due t...
Accurate streamflow prediction remains challenging due to the nonlinear and dynamic nature of rainfall-runoff processes. Conceptual hydrological model...
BACKGROUND: Inference-time retrieval augmentation is increasingly used to improve the traceability and verifiability of large language model (LLM) app...