Latest AI and machine learning research in risk management for healthcare professionals.
BACKGROUND: Advance care planning (ACP) involves proactive communication about end-of-life care preferences among patients, families, and health care providers. In Chinese culture, older adults commonly delegate such care decisions to adult children, yet family reluctance-rooted in beliefs that aggressive treatments are beneficial-remains a major barrier to ACP participation. Existing intervention...
High-stress conversations with family members in distress are a common part of the intensive care unit (ICU) nursing environment. Novice critical care nurses may have limited opportunities to practice these interactions before encountering them in clinical care. Traditional simulation methods can support communication training but often require faculty time, standardized patients, programming, and...
Deep learning is transforming the study of animal sound, enabling the automated identification of species, individuals, behaviors, and ecological patt...
Societies are aging rapidly in parallel with the increasingly earlier onset of serious diseases in younger populations. These and other factors are cr...
BACKGROUND/AIMS: The growing use of generative artificial intelligence, especially chatbots, has motivated researchers to test the accuracy of health ...
BACKGROUND: Varicocele (VC) grading has long relied on qualitative assessments of venous diameter and reflux signals, lacking standardization. OBJECTI...
OBJECTIVE: This narrative review aims to identify and evaluate the available scientific literature on digital technologies assisting clinicians in per...
INTRODUCTION: The chicken chorioallantoic membrane (CAM) is a widely used in vivo model for studying angiogenesis and tumor growth in accordance with ...
BACKGROUND: Hypermobile Ehlers-Danlos syndrome (hEDS) is a multisystemic hereditary connective tissue disorder characterized by generalized joint hype...
BACKGROUND: Digital health technologies are transforming healthcare. There is limited research describing how these technologies have been applied by ...
BACKGROUND: Large language models (LLMs) are increasingly used in health care by nonprofessionals (ie, individuals without formal training in health-r...
To develop and rigorously validate a deep learning framework for CT-free positron emission tomography (PET) attenuation correction in non-small cell l...
RATIONALE AND OBJECTIVES: Opportunistic osteoporosis screening using chest CT is increasingly explored, yet conventional QCT models are calibrated at ...
Artificial intelligence (AI) predictive models demonstrate potential for transforming clinical decision-making across medicine. However, conventional ...
Central nervous system (CNS) toxicities remain a major cause of drug attrition and represent a persistent challenge in predicting neurological risk du...
BACKGROUND: AI is increasingly being integrated into health care, making it important to understand stakeholder preferences for AI-enabled technologie...
BACKGROUND: Electronic early warning/track-and-trigger systems (EW/TTS) are crucial for patient monitoring, detecting clinical deterioration (CD), and...
BACKGROUND: Patient safety investigation reports support organizational learning only when they are complete, usable, and sufficiently detailed. Conve...
This study systematically investigates the robustness of radiomics-based machine learning models to distribution shifts caused by variations in MRI ac...
INTRODUCTION: Language development is a key determinant of academic achievement and psychosocial outcome. Due to the therapeutic hypothermia procedure...