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Hospitals

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Enhancing generalization in a Kawasaki Disease prediction model using data augmentation: Cross-validation of patients from two major hospitals in Taiwan.

PloS one
Kawasaki Disease (KD) is a rare febrile illness affecting infants and young children, potentially leading to coronary artery complications and, in severe cases, mortality if untreated. However, KD is frequently misdiagnosed as a common fever in clini...

Implementation of Machine Learning Applications in Health Care Organizations: Systematic Review of Empirical Studies.

Journal of medical Internet research
BACKGROUND: There is a growing enthusiasm for machine learning (ML) among academics and health care practitioners. Despite the transformative potential of ML-based applications for patient care, their uptake and implementation in health care organiza...

Antimicrobial efficacy of an experimental UV-C robot in controlled conditions and in a real hospital scenario.

The Journal of hospital infection
BACKGROUND: Among no-touch automated disinfection devices, ultraviolet-C (UV-C) radiation has been proven to be one of the most effective against a broad spectrum of micro-organisms causing healthcare-associated infections.

Forecasting the future of smart hospitals: findings from a real-time delphi study.

BMC health services research
BACKGROUND: In concert with other digital technologies, artificial intelligence (AI) is shaping the vision of smart hospitals. The transformation into smart hospitals, however, is all but trivial due to the lack of financial and human resources, digi...

Intelligent imaging technology applications in multidisciplinary hospitals.

Chinese medical journal
With the rapid development of artificial intelligence technology, its applications in medical imaging have become increasingly extensive. This review aimed to analyze the current development status and future direction of intelligent imaging technolo...

Longitudinal Model Shifts of Machine Learning-Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals.

Journal of medical Internet research
BACKGROUND: In recent years, machine learning (ML)-based models have been widely used in clinical domains to predict clinical risk events. However, in production, the performances of such models heavily rely on changes in the system and data. The dyn...

Robotic versus manual disinfection of global priority pathogens at COVID-19-dedicated hospitals.

American journal of infection control
BACKGROUND: Twelve bacterial families identified as global priority pathogens (GPPs) pose the greatest threat to human health due to declining antibiotic efficacy. Robotics, a swift and contactless tool for disinfecting hospital surfaces, was sought ...

The Willingness of Doctors to Adopt Artificial Intelligence-Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data.

Journal of medical Internet research
BACKGROUND: Artificial intelligence-driven clinical decision support systems (AI-CDSSs) are pivotal tools for doctors to improve diagnostic and treatment processes, as well as improve the efficiency and quality of health care services. However, not a...

Current Use And Evaluation Of Artificial Intelligence And Predictive Models In US Hospitals.

Health affairs (Project Hope)
Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, appropriate, valid, effective, and safe, or FAVES...