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.