Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development

Tyler J. Bradshaw, Ronald Boellaard, Joyita Dutta, Abhinav K. Jha, Paul Jacobs, Quanzheng Li, Chi Liu, Arkadiusz Sitek, Babak Saboury, Peter J. H. Scott, Piotr J. Slomka, John J. Sunderland, Richard L. Wahl, Fereshteh Yousefirizi, Sven Zuehlsdorff, Arman Rahmim, Irène Buvat

Research output: Contribution to journalArticleAcademicpeer-review

26 Citations (Scopus)


The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations on technical best practices for developing AI algorithms in nuclear medicine are provided, beginning with general recommendations and then continuing with descriptions of how one might practice these principles for specific topics within nuclear medicine. This report was produced by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging.
Original languageEnglish
Pages (from-to)500-510
Number of pages11
JournalJournal of nuclear medicine : official publication, Society of Nuclear Medicine
Issue number4
Publication statusPublished - 1 Apr 2022


  • Algorithm
  • Artificial intelligence
  • Best practices
  • Computer/PACS
  • Research methods
  • Statistics

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