The rapid development of clinical artificial intelligence (AI) technologies has outpaced the
development of robust regulatory and clinical safety mechanisms. AI systems are cleared for …

Background Artificial intelligence (AI) research in healthcare is accelerating rapidly, with
potential applications being demonstrated across various domains of medicine. However …

Despite artificial intelligence (AI) technology progresses at unprecedented rate, our ability to
translate these advancements into clinical value and adoption at the bedside remains …

Despite artificial intelligence (AI) technology progresses at unprecedented rate, our ability to
translate these advancements into clinical value and adoption at the bedside remains …

Artificial intelligence (AI) applications in healthcare offer the promise of improved decision
making for clinicians, and better healthcare outcomes for patients. While technical AI …

Importance Given the importance of rigorous development and evaluation standards
needed of artificial intelligence (AI) models used in health care, nationwide accepted …

Increased scrutiny of artificial intelligence (AI) applications in healthcare highlights the need
for real-world evaluations for effectiveness and unintended consequences. The complexity …

Clinical evaluation provides the necessary evidence that healthcare interventions are safe,
effective, and likely to bring benefit to patients and healthcare system. While a large volume …

Objective: The objective of this scoping review is to describe the scope and nature of
research on the monitoring of clinical artificial intelligence (AI) systems. The review will …

Background: Artificial intelligence (AI) applications that utilize machine learning are on the
rise in clinical research and provide highly promising applications in specific use cases …