… any specific clinical department, we believe that AI-QI entities should span clinical departments.
Such a group can be hosted by existing structures, such as a department of Biostatistics …

… First, we review clinical AI applications that provide decision support more broadly and … a
specific clinical domain. Second, we focus on studies that reported the evaluation of clinical AI …

… of machine learning, reinforcement learning, and deep learning are well-suited to deal with
such data. The authors in this paper review current applications of AI in clinical … by clinical …

… machine learning classifiers to distinguish patients with COVID-19 from pre-pandemic
controls, using electronic health record data for patients presenting to the emergency department …

… of patients at the emergency department is critical to inform … model that learns from routine
clinical variables. Our AI prognosis … In order to verify performance in a real clinical setting, we …

… We systematically reviewed the literature on attitudes toward clinical AI. We summarised
current knowledge and offered guidance for future studies, with the ultimate goal of supporting …

… Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence
(AI… by integrating it into clinical practice. Reporting AI’s role in clinical practice is crucial for …

… clinical artificial intelligence modeling (MI-CLAIM). With this work, we are targeting
medical-algorithm designers, repository managers, manuscript writers and readers, journal editors, …

… their interest in developing AI solutions for clinical care. Moreover, a diverse repertoire of …
the convergence of AI and clinical care. Thus, this work presents AI clinical applications in a …

… A growing number of artificial intelligence (AI)-based clinical decision support systems
are … Early stage clinical evaluation is important to assess an AI system’s actual clinical …