Latest AI and machine learning research in domestic violence for healthcare professionals.
Accurate prognostication of mobility outcomes is essential to guide rehabilitation and manage patient expectations. The prognostic utility of neuroimaging and neurophysiological biomarkers remains uncertain when measured early post-stroke. This systematic review aimed to examine the prognostic capacity of early neuroimaging and neurophysiological biomarkers of mobility outcomes up to 24-months pos...
Early detection of autism spectrum disorder (ASD) improves outcomes, yet clinical assessment is time-intensive. Artificial intelligence (AI) may support screening in preschool children by analysing behavioural, neurophysiological, imaging, and biomarker data. To synthesise studies that applied AI in ASD assessment and evaluate whether the underlying data and AI approaches can distinguish ASD chara...
The aim of this study was to test whether open-source Large Language Models (LLMs) can match the diagnostic accuracy of proprietary models in annotati...
Missed opportunities for diagnosis (MODs), sometimes termed diagnostic errors, are a major cause of patient morbidity and mortality in the emergency d...
Childhood maltreatment is a well-established risk factor for substance misuse. However, it remains unclear whether risk for specific illicit substance...
Epilepsy affects approximately 50 million people worldwide, and seizures remain difficult to predict in onset, severity, and duration. Real-time seizu...
This study explored the association between low-dose computed tomography (LDCT)-derived body composition and melanoma incidence risk. LDCT scans from ...
Economic evaluations of artificial intelligence (AI) in healthcare are expanding rapidly, yet underlying costing methods remains heterogenous, and fre...
Artificial intelligence (AI) applied to routine electrocardiograms (ECGs) offers promise for screening of structural heart disease (SHD), yet broad cl...
Peer review processes may inadequately assess compliance with established reporting guidelines such as the Consolidated Standards of Reporting Trials ...
To prospectively evaluate the feasibility and performance of expedited screening mammogram interpretation for women identified as high-risk by a deep ...
Diagnostic error in high-stakes clinical environments remains a significant cause of preventable harm. While a new generation of customisable digital ...
Advances in clinical research methods are frequently published in biomedical journals, but identifying these articles remains challenging due to their...
Loneliness is a major psychological challenge in older adulthood, contributing to increased risks of depression, anxiety, and mortality. Conversationa...
Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted scr...
Prior work showed that state-of-the-art (mid-2025) large language models (LLMs) prompted with varying batch sizes can perform well on systematic revie...
Large language models (LLMs) are increasingly used in randomized clinical trial (RCT) screening, but their potential for sociodemographic bias remains...
Lymphoma diagnosis remains challenging due to diverse subtypes and nonspecific presentations. While prior research focused primarily on clinical accur...
Despite the agricultural sector’s consistently high injury rates, formal reporting is often limited, leading to sparse national datasets that hinder e...
Systematic reviews (SRs) are essential for evidence-based practice but remain labor-intensive, especially during abstract screening. This study evalua...