• Dtsch Arztebl Int · Jul 2023

    Review

    The Quality and Utility of Artificial Intelligence in Patient Care.

    • Kai Wehkamp, Michael Krawczak, and Stefan Schreiber.
    • Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Campus Lübeck, Kiel, Germany; Department for Medical Management, MSH Medical School Hamburg, Hamburg, Germany; Institute of Medical Informatics and Statistics, Christian-Albrechts-University of Kiel, University Medical Center Schleswig-Holstein Campus Kiel, Germany; Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, University Medical Center Schleswig-Holstein Campus Kiel, Germany.
    • Dtsch Arztebl Int. 2023 Jul 10; 120 (27-28): 463469463-469.

    BackgroundArtificial intelligence (AI) is increasingly being used in patient care. In the future, physicians will need to understand not only the basic functioning of AI applications, but also their quality, utility, and risks.MethodsThis article is based on a selective review of the literature on the principles, quality, limitations, and benefits AI applications in patient care, along with examples of individual applications.ResultsThe number of AI applications in patient care is rising, with more than 500 approvals in the United States to date. Their quality and utility are based on a number of interdependent factors, including the real-life setting, the type and amount of data collected, the choice of variables used by the application, the algorithms used, and the goal and implementation of each application. Bias (which may be hidden) and errors can arise at all these levels. Any evaluation of the quality and utility of an AI application must, therefore, be conducted according to the scientific principles of evidence-based medicine-a requirement that is often hampered by a lack of transparency.ConclusionAI has the potential to improve patient care while meeting the challenge of dealing with an ever-increasing surfeit of information and data in medicine with limited human resources. The limitations and risks of AI applications require critical and responsible consideration. This can best be achieved through a combination of scientific.

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