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Toward Global Validation Standards for Health AI

 
: Wenzel, M.; Wiegand, T.

:

IEEE communications standards magazine 4 (2020), Nr.3, S.64-69
ISSN: 2471-2825
Englisch
Zeitschriftenaufsatz
Fraunhofer HHI ()

Abstract
Machine learning (ML) and artificial intelligence (AI) methods hold great potential for healthcare, for example, for purposes of diagnosis or prognosis that include a wide range of pattern recognition tasks. Ensuring that health ML/AI models are trustworthy will consequently become increasingly important soon. The ITU/WHO focus group on "AI for Health" is working on validation standards for health AI that can help to assess the quality of the powerful but complex technologies in a comparable and transparent manner. In particular, standardized benchmarking can serve as a valuable tool to determine the merits and limits of different health ML/AI models. In this article, ongoing work of the ITU/WHO initiative is introduced and set into perspective with related digital health and AI standardization efforts.

: http://publica.fraunhofer.de/dokumente/N-615315.html