Latest AI and machine learning research in cultural competence for healthcare professionals.
Viral diseases pose a serious threat to global public health, agriculture, and biosecurity. Conventional antiviral strategies are often limited by an incomplete understanding of disease mechanisms, poor targeting precision, and slow response times. Emerging technologies are now reshaping the landscape of antiviral research. This review examines the roles of four key frontiers, including organoid m...
BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-rela...
BACKGROUND: Despite advances in epilepsy treatment options, selecting the appropriate therapy for an individual with epilepsy is a process of trial an...
Advances in generative artificial intelligence (GenAI) have prompted interest in its application in sensitive fields, including mental health. Yet the...
Machine learning bias is a persistent challenge because it can create unfair outcomes, limit generalization, and reduce trust in real-world applicatio...
Many insects manipulate plants by injecting effector proteins. In one extreme example of this molecular "hijacking," Hormaphis cornu aphids inject bic...
BACKGROUND: AI is increasingly being explored as a tool to enhance efficiency, access, and diagnostic accuracy in mental health care. However, the per...
BACKGROUND: Augmented reality (AR) has emerged as a promising tool to enhance surgical precision during robot-assisted partial nephrectomy (RAPN), par...
Cancer remains one of the leading global health burdens, with increasing complexity in genomic, imaging, and clinical datasets presenting significant ...
BACKGROUND: Viral communities of the upper aerodigestive tract represent an important component of the human microbial ecosystem but remain poorly cha...
Multiple instance learning (MIL) has emerged as the dominant paradigm for whole slide image (WSI) analysis in computational pathology, achieving stron...
BACKGROUND: Artificial intelligence (AI) is transforming global health care through innovations in deep learning, generative models and agentic AI sys...
The discrimination of structurally similar biothiols remains a critical challenge in clinical diagnostics, as conventional nanozyme-based sensor array...
Accurate breast tumor segmentation in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is vital for diagnosis and treatment planning. De...
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples ...
INTRODUCTION: Cancer-related symptoms including pain, fatigue, depression, anxiety, and malnutrition drive poor quality of life and adverse clinical o...
BACKGROUND: Artificial intelligence-assisted early warning systems (AI-EWS) are increasingly integrated into critical care, yet little is known about ...
BACKGROUND: Real-world evidence (RWE) is increasingly used to inform regulatory and payer policy decisions and health technology assessment, yet appra...
BACKGROUND: Prior authorization (PA) is intended to support appropriate use and spending of services and medications, yet 1 in 6 insured adults report...
PURPOSE OF REVIEW: We examined the landscape of publicly available cardiac imaging datasets to assess how their distribution and construction shape bi...