Artificial intelligence (AI) tools are of great interest to healthcare organizations for their
potential to improve patient care, yet their translation into clinical settings remains …

Objective To identify factors influencing implementation of machine learning algorithms
(MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a …

The use of data-driven technologies such as Artificial Intelligence (AI) and Machine Learning
(ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced …

Objective: An ethical framework for the use of large language models (LLMs) is urgently
needed to shape how natural language processing (NLP) tools are used for healthcare …

When integrating AI tools in healthcare settings, complex interactions between technologies
and primary users are not always fully understood or visible. This deficient and ambiguous …

Responsible design of AI systems is a shared goal across HCI and AI communities.
Responsible AI (RAI) tools have been developed to support practitioners to identify, assess …

Artificial intelligence (AI) methods applied to healthcare problems have shown enormous
potential to alleviate the burden of health services worldwide and to improve the accuracy …

The SCM, developed by James Reason in the 1990s, is a widely recognized and influential
model used to understand and manage complex systems and their associated risks. The …

Healthcare delivery organizations (HDOs) in the US must contend with the potential for AI to
worsen health inequities. But there is no standard set of procedures for HDOs to adopt to …

Machine learning (ML) solutions are increasingly entering healthcare. They are complex,
sociotechnical systems that include data inputs, ML models, technical infrastructure and …