Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Credit card fraud detection is a difficult applied machine learning problem. It combines extreme class imbalance, temporal non-stationarity, and a sharp cost gap between missed fraud and false alarms. This paper presents an end-to-end experimental framework for fraud detection on the benchmark European transaction dataset (284,807 transactions; fraud prevalence 0.173%). A strict no-data-leakage pr...
BACKGROUND: Although artificial intelligence (AI) is increasingly transforming healthcare systems, its systematic integration into undergraduate medical education (UME) remains limited. Despite widespread recognition of AI's potential to enhance clinical practice, AI-related competencies are still inadequately embedded in most medical curricula, even though medical students generally express posit...
In the field of electrocatalysis, the industrial application of high-loading electrodes faces a fundamental contradiction: traditional designs based o...
CONTEXT: High-energy density materials (HEDMs) are indispensable for defense and a wide range of industrial applications. A core challenge in their de...
Chemicals of emerging concern (CECs) pose major challenges for wastewater treatment plants because they are difficult to biodegrade, persist in the en...
Large language models (LLMs) show great potential for clinical decision-making, yet most applications remain narrow, task-specific chat tools rather t...
Accurate automated segmentation of Lumbar Spine Structures (LSS) in Magnetic Resonance Imaging (MRI) is important for effective diagnosis and treatmen...
Large language models are increasingly applied in medical education, but their role in clinical pathology remains uncertain. We conducted a prospectiv...
INTRODUCTION: The integration of artificial intelligence (AI) into healthcare is transforming nursing practice, introducing both opportunities and cha...
OBJECTIVE: To systematically characterise United States Food and Drug Administration (FDA) authorised urology-specific artificial intelligence (AI)-en...
Magnetic random-access memory (MRAM) is emerging as a pivotal technology for next-generation non-volatile spintronics. At its core lies the magnetic t...
The increasing complexity of cardiovascular procedures, regulatory constraints, and heightened patient safety requirements have necessitated a fundame...
BACKGROUND: Digital health offers opportunities for safe, equitable, and accessible care, and its integration into respiratory care is a strategic pri...
Internal medicine manages patients with multiple comorbidities or rare diseases, for whom the scientific literature often provides limited guidance. P...
Quantum or quantum-inspired Ising machines have recently shown promise in solving combinatorial optimization problems in a short time. Real-world and ...
Conventional immune checkpoint inhibitors (ICIs) remain largely ineffective in microsatellite-stable metastatic colorectal cancer (MSS mCRC), where lo...
BACKGROUND: Large language models (LLMs) can generate structured educational content at scale, yet their role in postgraduate radiology training remai...
The heterogeneous acquisition, variability of orientation, and subtle lesions continue to challenge the screening of diabetic retinopathy through colo...
The rapid proliferation of distributed energy resources (DERs) in modern power grids introduces unprecedented complexity into real-time dispatch sched...
This study was aimed at evaluating the effectiveness of artificial intelligence (AI) in detecting jaw cysts and tumors, analyzing lesion content, and ...