Latest AI and machine learning research in cultural competence 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...
Proteins and peptides underpin essential biological functions and technological applications, from targeting disease-relevant interactions to providing broad enzymatic activities. However, engineering molecules with desired properties remains difficult, owing to complex sequence-structure-function relationships and the lack of data on specific systems. Experimental selection strategies, including ...
Machine learning has been successfully applied to accelerate Mixed-Integer Linear Programming (MILP) solvers. However, the learning-based solvers ofte...
Accurate seismic fault detection is essential for reliable structural interpretation, reservoir characterization, and drilling risk mitigation. Conven...
The absence of publicly available, large-scale, high-quality datasets for Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has signific...
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...
It is estimated that, globally, the mean point prevalence of diagnosable mental disorders in children and adolescents is higher than 11%, and around h...
Radiation resistance in bacteria is a critical trait with implications for biotechnology, medicine and environmental science. Deinococcus species poss...
Dietary intake data are essential for understanding diet-disease relationships, informing policy, and evaluating nutrition interventions. This is part...
BACKGROUND: Nurses are concerned that artificial intelligence (AI) could undermine the holistic, intuitive, and experience-based clinical judgment tha...
BACKGROUND: Despite the increasing number of studies on prediction models for identifying the risk of postpartum post-traumatic stress disorder (PP-PT...
PROBLEM: Traditional epidemiological surveillance methods are often limited by delays in reporting and fragmented data systems. Saudi Arabia faces add...
Atomic-scale metal clusters, which bridge the gap between nanoparticles and single-atom catalysts, show pronounced structure-sensitive reactivity that...
OBJECTIVE: This study aimed to externally validate the screening performance of a pro-social (equitable, accessible), explainable AI (XAI)-guided mobi...
Depression, anxiety, and stress are significant global health burdens worsened by restricted access to care. Conversational agents (CAs), encompassing...
OBJECTIVES: Chat Generative Pretrained Transformer (ChatGPT) is a widely adopted tool that can provide immediate parenting guidance. The aim of this s...
OBJECTIVES: To evaluate the impact of automation and anchoring bias in artificial intelligence (AI)-assisted mammography interpretation and to assess ...
BACKGROUND: The issue of population aging has emerged as a critical global challenge, driving the imperative for effective self-care and scalable heal...
Despite many success stories along the path of Artificial Intelligence's (AI) rise in healthcare, there are comparably many reports of significant sho...