Latest AI and machine learning research in domestic violence for healthcare professionals.
Tight glycemic control reduces acute complications (hypoglycemia, hyperglycemia) and long-term microvascular/macrovascular risks. The application of Artificial Intelligence (AI) to support optimal blood glucose management appears promising, however, its adoption at the bedside is still restricted. A recurring source of confusion is that short-horizon glucose forecasting and automated closed-loop c...
BACKGROUND: Optimal timing of extubation in mechanically ventilated patients remains a major challenge in intensive care. Machine learning (ML) models have been increasingly proposed to support clinical decision-making, yet their predictive performance and readiness for clinical application in extubation outcomes remain uncertain. This study aimed to evaluate the predictive performance and clinica...
The use of artificial intelligence (AI) is anticipated to transform mental health care. However, the rapid research growth in this field has outpaced ...
Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition requiring early and accurate identification to optimize outco...
OBJECTIVE: To argue that diagnostic and predictive AI should be evaluated by both classification performance and the downstream work their outputs cre...
INTRODUCTION: Trigger tool methodologies have become important approaches for detecting adverse events in hospital care because they identify more har...
Image quantification is central to modern biomedical research. However, the reproducibility of image-based studies remains a persistent challenge due ...
BACKGROUND: Accurate reporting in nuclear medicine is essential for clinical decision-making. Trainees often generate preliminary reports with variabl...
BACKGROUND: Medical adherence is traditionally defined as the extent to which a person's behavior corresponds with agreed-upon recommendations from a ...
BACKGROUND: Machine learning (ML), deep learning (DL) and other predictive modelling approaches are increasingly applied to predict antiretroviral the...
BACKGROUND: Lung cancer (LC) remains the deadliest cancer, often diagnosed at advanced stages. Screening reduces mortality in high-risk individuals. E...
Orbital reconstruction after trauma or pathology requires precise restoration of anatomical symmetry to prevent functional and aesthetic impairment. A...
PURPOSE: This study aimed to evaluate the validity and feasibility of home obstructive sleep apnea screening using a sleep sound analysis smartphone a...
INTRODUCTION: This descriptive study aimed to longitudinally evaluate the performance of contemporary large language models - ChatGPT-5, Gemini 2.5 Fl...
The recent rapid development of mobile and wearable sensing technologies and computational modeling has allowed for high-density and continuous measur...
Radiomics applied to two-dimensional breast ultrasound has emerged as a potential noninvasive approach for differentiating benign from malignant breas...
Deep learning (DL) is increasingly applied to automate brain tumor classification from magnetic resonance imaging (MRI), yet meaningful clinical deplo...
Developmental neurotoxicity (DNT) represents a critical yet underevaluated toxicity endpoint within current chemical safety assessment frameworks, par...
BACKGROUND/AIM: To determine the comparative efficacy of trained versus untrained generative artificial intelligence platforms in providing multiple-c...
Drug repurposing involves the discovery of new therapeutic uses of existing drugs that have already been approved by the regulatory authorities. It pr...