Effective monitoring of online AI decision-making algorithms in just-in-time adaptive interventions.

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Bibliographic Details
Title: Effective monitoring of online AI decision-making algorithms in just-in-time adaptive interventions.
Authors: Trella AL; Department of Computer Science, Harvard University, Cambridge, MA, USA., Ghosh S; Department of Computer Science, Harvard University, Cambridge, MA, USA. susobhan_ghosh@g.harvard.edu., Bonar EE; Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA., Coughlin L; Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA., Doshi-Velez F; Department of Computer Science, Harvard University, Cambridge, MA, USA., Guo Y; Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA., Hung PY; Institute for Social Research, University of Michigan, Ann Arbor, MI, USA., Nahum-Shani I; Institute for Social Research, University of Michigan, Ann Arbor, MI, USA., Shetty V; School of Dentistry & Engineering, University of California, Los Angeles, Los Angeles, CA, USA., Walton M; Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA., Yan I; Department of Computer Science, Harvard University, Cambridge, MA, USA., Zhang KW; Mathematics Department, Imperial College London, South Kensington, London, UK., Murphy SA; Department of Computer Science, Harvard University, Cambridge, MA, USA.; Department of Statistics, Harvard University, Cambridge, MA, USA.
Source: NPJ digital medicine [NPJ Digit Med] 2026 May 04. Date of Electronic Publication: 2026 May 04.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-026-02669-4