Key points are not available for this paper at this time.
Artificial intelligence (AI) is increasingly of tremendous interest in the medical field. How-ever, failures of medical AI could have serious consequences for both clinical outcomes and the patient experience. These consequences could erode public trust in AI, which could in turn undermine trust in our healthcare institutions. This article makes 2 contributions. First, it describes the major conceptual, technical, and humanistic challenges in medical AI. Second, it proposes a solution that hinges on the education and accreditation of new expert groups who specialize in the development, verification, and operation of medical AI technologies. These groups will be required to maintain trust in our healthcare institutions.
Building similarity graph...
Analyzing shared references across papers
Loading...
Quinn et al. (Tue,) studied this question.
synapsesocial.com/papers/69de85337ed287395e5597b8 — DOI: https://doi.org/10.1093/jamia/ocaa268
Thomas P. Quinn
Australian Research Council
Manisha Senadeera
Deakin University
Stephan Jacobs
Deakin University
Journal of the American Medical Informatics Association
The University of Melbourne
Deakin University
Building similarity graph...
Analyzing shared references across papers
Loading...
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: