Latest AI and machine learning research in surveillance for healthcare professionals.
PURPOSE: To evaluate the incidence of uterine tachysystole and determine if nurses' management of tachysystole using an artificial intelligence-enabled clinical decision support (cEFM-aiCDS) alert system alone and in combination with an education module about tachysystole could be improved. STUDY DESIGN METHODS: Phase I involved a pre-post study design comparing the incidence and management of tac...
Mosquito-borne diseases remain a major global health challenge, disproportionately impacting low- and middle-income countries. Despite traditional control and surveillance efforts, many of these diseases are resurging, driven by climate change, urbanisation, and global trade and travel. In recent years, machine learning, a subset of artificial intelligence, has emerged as a powerful tool for suppo...
BACKGROUND: Artificial intelligence (AI) is increasingly applied in endourology to enhance surgical planning, risk stratification, and outcome predict...
OBJECTIVES: To evaluate whether collaborative assistance from an artificial intelligence-based tool that proposes partial radiology report content can...
BACKGROUND: Artificial intelligence (AI) is expanding across various medical fields, with machine learning (ML) being increasingly used to enhance pat...
INTRODUCTION: Multidrug-resistant organisms, including carbapenem-resistant Gram-negative bacilli (CRGNB), have a heavy health and economic burden in ...
BACKGROUND: Intimate partner violence (IPV) remains a major global public health and humanrights challenge, with a disproportionate burden in sub-Saha...
OBJECTIVES: Accurate prediction models for imported infectious diseases are essential for early warning, cross-border surveillance, and resource alloc...
Ammonia (NH3) is a promising carbon-free energy carrier, and its synthesis is a key process in the chemical industry. While the Haber-Bosch process re...
OBJECTIVE: The primary objective of this study is to enhance the detection and staging of pressure injuries using machine learning capabilities for pr...
BACKGROUND: Klebsiella pneumoniae complex (Kp) is a relevant neonatal pathogen colonizing preterm infants. While outbreak investigations often focus o...
BACKGROUND: Artificial intelligence (AI) and computerized clinical decision support systems (CDSS) are increasingly applied in intensive care, yet the...
OBJECTIVE: Given China's rapid population ageing and substantial stroke burden, understanding the epidemiology of vascular cognitive impairment (VCI) ...
CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, an...
INTRODUCTION: Premature mortality (PM) is a concept applied in public health, epidemiology, medicine, demography and economics. Its conceptualisations...
This scoping review aimed to answer the question: to what extent do artificial intelligence applications in dental and orthopedic skeletal imaging dem...
Reproducibility of machine learning applications in clinical informatics heavily relies on data preparation. However, preprocessing pipelines are not ...
Chronic hepatitis B remains a major global health challenge despite the advances in antiviral therapy. Although hepatitis B surface antigen (HBsAg) se...
BACKGROUND: Recent advances in computational pathology enables AI-assisted diagnosis and risk stratification of breast cancer. This advance in technol...