Background Integrating artificial intelligence (AI) in healthcare settings has the potential to
benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness …

AI assistance in decision-making has become popular, yet people's inappropriate reliance
on AI often leads to unsatisfactory human-AI collaboration performance. In this paper …

Objectives To identify the barriers and facilitators to the successful implementation of
imaging-based diagnostic artificial intelligence (AI)-assisted decision-making software in …

Integration of artificial intelligence (AI) into clinical decision support systems (CDSS) poses a
socio-technological challenge that is impacted by usability, trust, and human-computer …

ABSTRACT Aim/Purpose The main goal of this study is to investigate the factors affecting
students' satisfaction and continuous usage of ChatGPT in an educational context, using the …

This systematic review examines the evolution and current landscape of eXplainable
Artificial Intelligence (XAI) in Clinical Decision Support Systems (CDSS), highlighting …

Abstract Clinical Decision Support Systems (CDSS) are essential tools in contemporary
healthcare, enhancing clinicians' decisions and patient outcomes. The integration of artificial …

Artificial intelligence (AI) has shown promise in revolutionizing medical triage, particularly in
the context of the rising prevalence of kidney-related conditions with the aging global …

AI systems can bring great benefits to our healthcare systems, eg by improving patient
outcomes. Yet implementing them into clinical practice remains challenging. To bridge the …

Despite recent advances in cancer treatments that prolong patients' lives, treatment-induced
cardiotoxicity remains one severe side effect. The clinical decision-making of cardiotoxicity is …