Latest AI and machine learning research in risk management for healthcare professionals.
Machine learning struggles with imbalanced data. Although several mitigation approaches exist, their application depends on the extent of imbalance. To determine the latter, a protocol was developed. Across 428 synthetic and 70 real datasets, 8 imbalance measures were benchmarked and evaluated using multiple classifiers, metrics, and correlation coefficients. The coding environment, data preparati...
BACKGROUND: Artificial intelligence (AI) and computerized clinical decision support systems (CDSS) are increasingly applied in intensive care, yet their clinical impact remains uncertain, as most studies focus on model development rather than prospective evaluation. OBJECTIVES: To identify randomized controlled trials (RCTs) evaluating AI-based or CDSS interventions intended to influence real-time...
AI is reshaping medical research and healthcare delivery, yet the translation of AI innovations into clinically approved medical devices remains limit...
OBJECTIVE: The use of ambient AI documentation tools is rapidly growing in US hospitals and clinics. Such tools generate the first draft of clinical n...
INTRODUCTION: Dementia imposes significant care and financial burdens on families and countries globally. While high-quality home-based care is crucia...
INTRODUCTION: Premature mortality (PM) is a concept applied in public health, epidemiology, medicine, demography and economics. Its conceptualisations...
Non-communicable diseases (NCDs) account for ~71% of all deaths globally, including 15 million premature deaths each year (deaths between 30-69 years ...
BACKGROUND: Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of sim...
Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 perc...
INTRODUCTION: The growing volume of primary research and the increasing demand for timely, high-quality evidence syntheses (ESs) have intensified inte...
BACKGROUND: Postoperative delirium (POD) is a prevalent and serious complication in older surgical patients, linked to prolonged hospitalization, high...
Guide dogs play essential roles in supporting independence and well-being of visually impaired people. High attrition rates underscore the need for mo...
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) remains one of the most devastating types of stroke, with high mortality and long-term disabili...
BACKGROUND: Deep learning (DL)-based artificial intelligence (AI) models, the fourth generation in autosegmentation, have been adopted both for commer...
OBJECTIVE: To systematically evaluate training sample size adequacy in externally validated machine learning (ML)-based radiomics models published in ...
BACKGROUND: Accurate assessment of burn depth and area are required to guide treatment and inform prognosis. Currently this assessment relies on subje...
OBJECTIVE: Efficient and high-quality history taking is central to vestibular diagnosis, but it is often constrained by limited consultation time and ...
PURPOSE: The conventional computed tomography (CT)-based consultation to simulation process for hippocampal-sparing whole-brain radiation therapy (HS-...
Oral potentially malignant disorders (OPMDs) can directly progress to cancer, necessitating accurate risk prediction to guide clinical intervention. H...
Tobacco quality inspection plays a vital role in ensuring standardized processing, reducing economic losses, and improving industrial automation. Howe...