Latest AI and machine learning research in surveys for healthcare professionals.
BACKGROUND: Urine cytology is a noninvasive and valuable tool for detecting urothelial carcinoma but suffers from variable sensitivity and observer dependency. Artificial intelligence (AI) may enhance the diagnostic accuracy and efficiency of urine cytology. The objective of this study was to develop and validate an AI-based cytology system for urothelial carcinoma detection in both clinical and s...
Gaussian mixture regression (GMR) and direct inverse analysis (DIA) are powerful tools for molecular, material, and process design, but their reliability decreases when extrapolation occurs beyond the training data. To address this challenge, an index of extrapolation (IoE) that evaluates extrapolation potential and prediction trustworthiness in both forward and inverse analyses of GMR models is p...
BACKGROUND: Chemotherapy-related toxicities often lead to unscheduled health care use and diminished quality of life. Digital health interventions, su...
The presence of active pharmaceutical ingredients (APIs) in aquatic environments calls for greater attention to the risks these substances may pose, p...
OBJECTIVES: The increasing use of machine learning (ML) in clinical care makes fairness a central issue. Fairness, defined as the absence of dispariti...
We evaluate the performance of targeted maximum likelihood estimation (TMLE) for estimating the average treatment effect in missing data scenarios und...
BACKGROUND: Background Clinical documentation is a major contributor to clinician workload and burnout, with physicians spending more than half of the...
BACKGROUND: Proficiency in cytopathologic diagnosis depends heavily on extensive hands-on practice and immediate error correction. Traditional teachin...
This methodological study aimed to develop a reliable and valid scale to measure nursing students' attitudes toward the use of ChatGPT in nursing educ...
PURPOSE: This study explored large language models (LLMs) as a scalable solution to the global shortage and uneven distribution of ophthalmologists, p...
INTRODUCTION: Prospective prediction of mental health risk is critical for early intervention to reduce the burden of depression, anxiety, and cogniti...
PURPOSE: A prior national survey of U.S. hematology/oncology (H/O) fellowship curricula demonstrated substantial heterogeneity and limited protected d...
Dietary intake data are essential for understanding diet-disease relationships, informing policy, and evaluating nutrition interventions. This is part...
BACKGROUND: Despite the increasing number of studies on prediction models for identifying the risk of postpartum post-traumatic stress disorder (PP-PT...
Fat mass index (FMI) reflects adiposity normalized for height and may provide information beyond body mass index. Evidence on its relationship with de...
Depressive symptoms frequently co-occur with hearing impairment in older adults, yet available prediction tools for this high-risk subgroup remain lim...
INTRODUCTION: Traumatic dental injuries (TDIs) require prompt and accurate guidance, yet little is known about how the prompting influences the qualit...
The European research landscape for developing new diagnostic, preventive, and therapeutic interventions is fraught with challenges. Scarcity of quali...
OBJECTIVES: Artificial Intelligence (AI) is increasingly integrated into medicine, including otolaryngology. However, concerns remain regarding the ac...
OBJECTIVES: Chat Generative Pretrained Transformer (ChatGPT) is a widely adopted tool that can provide immediate parenting guidance. The aim of this s...