Recent advances in AI combine large language models (LLMs) with vision encoders that
bring forward unprecedented technical capabilities to leverage for a wide range of …

Clinical practice guidelines, care pathways, and protocols are designed to support evidence-
based practices for clinicians; however, their adoption remains a challenge. We set out to …

Aim: This study aims to investigate the influence of medical explainable artificial intelligence
(XAI) on the innovation behaviour of nurses, as well as explore the dual‐pathway mediating …

This paper investigates the impact of personalized AI communication on clinical outcomes in
breast cancer diagnosis. Our study examines how different AI communication styles …

Community health workers (CHWs) provide last-mile healthcare services but face
challenges due to limited medical knowledge and training. This paper describes the design …

Hemorrhage, or severe blood loss due to injury, is a leading cause of preventable deaths
after injury. This study uses and extends activity theory to understand the dynamics of team …

Generative AI has the potential to transform knowledge work, but further research is needed
to understand how knowledge workers envision using and interacting with generative AI. We …

There is a growing need to understand how digital systems can support clinical decision-
making, particularly as artificial intelligence (AI) models become increasingly complex and …

Advances in artificial intelligence (AI) enable impressive new technical capabilities:
computers can diagnose diseases, translate between languages, and drive cars …

Despite recent advancements, real-world use of Artificial Intelligence (AI) in radiology
remains low, often due to the mismatch between AI offerings and the situated challenges …