Artificial Intelligence (AI) in medical applications holds great promise. However, the use of
Machine Learning-based (ML) systems in clinical practice is still minimal. It is uniquely …

Recent advances in AI and machine learning (ML) promise significant transformations in the
future delivery of healthcare. Despite a surge in research and development, few works have …

Background Increasing attention is being given to the analysis of large health datasets to
derive new clinical decision support systems (CDSS). However, few data-driven CDSS are …

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 …

The development of Artificial intelligence (AI) is accelerating and promising to impact
healthcare. Advancements in processing chips and Machine Learning (ML) have made …

Objectives To define requirements that condition trust in artificial intelligence (AI) as clinical
decision support in radiology from the perspective of various stakeholders and to explore …

Background Artificial intelligence–based clinical decision support (AI-CDS) tools have great
potential to benefit intensive care unit (ICU) patients and physicians. There is a gap between …

Objective Understand public comfort with the use of different data types for predictive models
Materials and Methods We analyzed data from a national survey of US adults (n= 1436) …

Hypotension during perioperative care, if undetected or uncontrolled, can lead to serious
clinical complications. Predictive machine learning models, based on routinely collected …

Artificial Intelligence and Machine Learning (AI/ML) tools are changing the landscape of
healthcare decision-making. Vast amounts of data can lead to efficient triage and diagnosis …