Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
Graph neural networks (GNNs) have significantly advanced social recommendation; however, existing methods often homogenize diverse social influences and neglect latent item-item correlations, limiting their ability to model complex user preferences. To overcome these limitations, we propose DiffRSG, a novel framework that integrates neural latent information diffusion with explicit rule-guided rea...
BACKGROUND: Dental pulp calcifications, including pulp stones and diffuse calcific changes, can complicate endodontic access, canal negotiation, and treatment planning. Artificial intelligence may support radiographic detection of these findings, but the available evidence remains limited and methodologically heterogeneous. This scoping review mapped peer-reviewed studies that applied artificial i...
The increasing digitalization of healthcare necessitates laboratory data interoperability to ensure reliable clinical decision-making, efficient data ...
Artificial intelligence (AI) has emerged as a promising tool in forensic sciences, offering new opportunities for personal identification through auto...
BACKGROUND: Heart failure is not only a prevalent disease with a high mortality rate, but also generates high costs for healthcare systems. By trainin...
With the advancement of artificial intelligence, molecular design based on generative models offers novel approaches to accelerate drug discovery. How...
Purpose To evaluate the pooled diagnostic accuracy of externally tested AI models for malignancy classification of lung nodules on chest CT. Materials...
BACKGROUND: Paediatric chest imaging is central to diagnosing respiratory and cardiopulmonary disease, particularly in low- and middle-income countrie...
The diagnosis of prostate cancer rests on the histopathological evaluation of prostate needle core biopsy specimens (NCBS) supplemented by immunohisto...
Contrast-enhanced computed tomography (CECT) of the abdomen and pelvis is widely used for diagnostic imaging but contributes substantially to cumulati...
INTRODUCTION: Hospitalized patients with heart failure (HF) frequently receive multiple high-risk intravenous (IV) medications, placing them at a subs...
INTRODUCTION: Artificial intelligence (AI)-powered chatbots are increasingly integrated into healthcare to support administrative processes, health ed...
BACKGROUND: Accurate segmentation of acute ischemic stroke (AIS) lesions on neuroimaging is essential for diagnosis, treatment decision-making, and pr...
INTRODUCTION/AIMS: Electrodiagnostic (EDX) studies comprise nerve conduction studies (NCS) and needle electromyography (EMG). However, EDX reporting i...
BACKGROUND: Urine cytology is a noninvasive and valuable tool for detecting urothelial carcinoma but suffers from variable sensitivity and observer de...
BACKGROUND: Child neglect, defined as a parent or guardian's failure to provide basic needs such as food, clothing, shelter, or medical care, is a wid...
PURPOSE: Foundation models pretrained on structured electronic health record (EHR) data promise improved predictive performance, sample efficiency and...
AIM: The aim of this study was to explore the perspectives of midwifery academics regarding the integration of Artificial Intelligence (AI) into midwi...
BACKGROUND: Artificial intelligence (AI), including deep learning and large language models, is increasingly reshaping healthcare and medical educatio...
AIM: To identify and differentiate workload patterns across shifts and to provide evidence for optimizing nursing workforce allocation in emergency de...