Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
Despite advances in deep learning and transformer architectures, prior reviews have focused narrowly on traditional clinical decision support systems (CDSS) or single medical domains, leaving significant gaps in understanding contemporary AI-driven predictive tools. This systematic review and meta-analysis evaluated the predictive performance of artificial intelligence-based CDSS (AI-CDSS) across ...
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and related dementias remains challenging because no single biomarker sufficiently captures the complex and multifactorial nature of the underlying pathology. In recent years, multimodal artificial intelligence (AI) models capable of integrating heterogeneous data sources-such as neuroimaging, fluid biomarkers, genetics, and cognitive assessm...
AIM: The aim of this study is to assess nurse practitioner students' perceptions and engagement with Isabel's artificial intelligence (AI) based diffe...
PURPOSE: To map contemporary uses of artificial intelligence (AI) to identify conventional and unconventional risk factors for sports injuries in athl...
BACKGROUND: The integration of artificial intelligence (AI) into virtual emergency care represents a potentially transformative approach to healthcare...
BACKGROUND: Diet-related chronic conditions are major contributors to global morbidity and mortality. Effective management of these conditions require...
Solid-state electrolytes (SSEs) are attractive for next-generation lithium-ion batteries due to improved safety and stability, but their low room-temp...
Infrared and visible image fusion aims to generate a fusion image that integrates complementary information from both modalities. Current deep learnin...
BACKGROUND: The changing working conditions in routine radiological reporting require the use of new methods, such as the implementation of artificial...
BACKGROUND: Otitis media (OM) is a common pediatric infection worldwide. Conventionally, accurate diagnosis depends on in-person pneumatic otoscopy, w...
The prevalence of generative artificial intelligence (GenAI) usage related to sexualized images amongst adolescents is a critical emerging research ar...
AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of ...
INTRODUCTION: Diagnostic errors remain a critical patient safety concern, yet teaching diagnostic reasoning is challenging due to its complex, context...
BACKGROUND: Routine healthcare data are increasingly stored in electronic health records (EHRs), presenting an exciting opportunity to leverage machin...
Integrating artificial intelligence (AI) into maternal and neonatal health (MNH) offers significant opportunities for enhancing patient care through a...
BACKGROUND: Radiologists often employ diagnostic certainty phrases (DCPs) to convey levels of confidence in imaging interpretations. Prior research in...
Prostate magnetic resonance imaging (MRI) has become a crucial tool in diagnosing and managing prostate cancer, mainly by helping to avoid unnecessary...
BACKGROUND: Adult-type gliomas are among the most prevalent and lethal primary central nervous system tumors, where prompt and accurate diagnosis is e...
BACKGROUND: Early diagnosis of oral squamous cell carcinoma (OSCC) remains challenging, with survival largely stage-dependent at presentation. Artific...
Aspect Sentiment Triplet Extraction (ASTE) is an emerging subtask of Aspect-Based Sentiment Analysis (ABSA), aiming to extract aspect terms, opinion t...