Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
AIM: To examine the perinatal experiences of at-risk mothers and their engagement with mobile-health-based care. DESIGN: A qualitative descriptive study. METHODS: One-to-one semi-structured interviews were conducted with 30 at-risk mothers, defined as those who were single, had low income, were at risk of depression, had adverse childhood experiences, gave birth to a baby with congenital disorders...
AIMS: The study focused on nurses' familiarity with, beliefs about, and attitudes towards artificial intelligence, aiming to identify configurations of necessary and sufficient conditions associated with strong intentions to use artificial intelligence-based health technologies in their clinical practice. DESIGN: Cross-sectional survey conducted online from mid-October 2023 through early February ...
Current 3D point-cloud semantic segmentation employs few-shot learning to lessen reliance on large-scale data. Previous prototype-based methods typica...
BACKGROUND: Artificial intelligence (AI) is increasingly integrated into surgical practice, offering enhanced decision-making, precision, and workflow...
Knowledge distillation (KD) is a proven technique for enhancing the performance of lightweight models in intelligent edge applications for remote sens...
AIMS: To predict nurses' turnover intention using machine learning techniques and identify the most influential psychosocial, organisational and demog...
BACKGROUND: Early detection of cancer reduces mortality and morbidity, but conventional screening methods often face challenges such as invasiveness, ...
Existing bipartite graph based methods commonly learn a consistent anchor graph across multiple views utilizing various optimization techniques to det...
OBJECTIVE: Researchers in otolaryngology-head and neck surgery (OHNS) have sought to explore the potential of large language models (LLMs), but many p...
Multi-modal analysis can provide complementary information and significantly aid in the early diagnosis and intervention of Alzheimer's Disease (AD). ...
AIMS: To (1) analyse managers' experiences with handling patient safety incident reports in an incident reporting software, identifying key challenges...
Artificial intelligence (AI), particularly machine learning (ML), is increasingly influencing pharmacovigilance (PV) by improving case triage and sign...
Medical devices are indispensable in modern healthcare. They enable the prevention, diagnosis, and treatment of diseases while enhancing patient outco...
BACKGROUND: Artificial intelligence (AI) applications for pediatric fracture diagnosis using radiographs have demonstrated growing potential in clinic...
Venous thromboembolism (VTE) remains a leading cause of cardiovascular morbidity and mortality, despite advances in imaging and anticoagulation. VTE a...
AIM: This study aimed to gain insight into the thoughts, perceptions and needs of nurses caring for older adults with cardiometabolic multimorbidity r...
This paper aims to identify key factors influencing elder abuse within the family and to further explore the heterogeneity of these factors across dif...
The activation of dihydrogen by transition-metal monoxide cations (MO) in the gas phase offers valuable mechanistic insight into multistate reactions....
This study, involving a cohort of 980 patients with arterial and/or venous events, evaluated the relative importance of genetic and traditional risk f...
Artificial intelligence (AI) and machine learning (ML) are transforming nephrology by enhancing diagnosis, risk prediction, and treatment optimization...