Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
BACKGROUND: Acute kidney injury (AKI) is a common complication following pediatric cardiac surgery, frequently leading to poor outcomes and even death in severe cases. Early prevention remains the primary intervention strategy. Studies have developed prediction models to identify at-risk children at an early stage. This study systematically evaluate existing AKI prediction models to support their ...
BACKGROUND: Global rehabilitation needs far exceed capacity, and artificial intelligence (AI) is proposed to extend access, personalise therapy, and support adherence. We aimed to synthesise evidence on clinical effectiveness, prognostic performance, and implementation feasibility of AI-enabled rehabilitation across conditions and care settings. METHODS: We conducted a mixed-methods systematic rev...
IMPORTANCE AND OBJECTIVE: Menopause is characterized by sustained estradiol decline affecting vasomotor, metabolic, skeletal, and neurobehavioral syst...
BACKGROUND: Periprosthetic joint infection (PJI) remains one of the most serious complications after joint arthroplasty, and accurate diagnosis contin...
The rapid integration of generative artificial intelligence (Gen AI) into academic writing has outpaced the establishment of consistent norms for resp...
BACKGROUND: The use of artificial intelligence (AI) has rapidly increased in metabolic and bariatric surgery (MBS) in recent years, necessitating a co...
PURPOSE: Retinal vascular features provide noninvasive biomarkers of systemic vascular health, and deep learning tools such as AutoMorph now enable th...
Artificial intelligence (AI)-powered computational methods, such as machine learning and natural language processing, are increasingly applied in deat...
INTRODUCTION: Digital health interventions have emerged as promising solutions to strengthen maternal, newborn and child health (MNCH) systems in low-...
OBJECTIVE: Screening for psychiatric risk in youth at the population level is often constrained by resource limitations and lengthy assessment tools. ...
BACKGROUND: Informed consent (IC) documents in spine surgery frequently lack procedure-specific risk data, quantitative complication rates, and discus...
BackgroundDigital technologies are reshaping leadership in nursing, making it essential to understand how digital leadership relates to attitudes towa...
BACKGROUND: Urogenital schistosomiasis caused by Schistosoma haematobium remains endemic in sub-Saharan Africa. Diagnosis traditionally relies on urin...
INTRODUCTION: This study aimed to evaluate the effectiveness of a generative artificial intelligence based simulated patient model in improving gyneco...
Health professions' education (HPE) research has evolved within an academic ecosystem. This paper works to put forth that generative artificial intell...
BACKGROUND: Depression is a pervasive global mental health issue, yet access to trained professionals remains severely limited. With the rapid advance...
BACKGROUND: The growing number of hypoglycaemia risk prediction models for Type 2 diabetes mellitus (T2DM) underscores the need for systematic evaluat...
Continuous glucose monitoring (CGM) has markedly advanced diabetes care by enabling real-time visualization of glycaemic variability, prevention of hy...
PURPOSE: To develop and validate deep learning models for predicting keratoconus progression risk using multimodal imaging and clinical data, enabling...
BACKGROUND: Participatory approaches (including co-research, co-design, Patient and Public Involvement [PPI], and Participatory Action Research [PAR])...