arXiv Machine Learning August 7, 2026 By Joshua P. Zitovsky, Yating Zou, Leslie Wilson, Michael R. Kosorok

Latent Utility Q-Learning for Preference-Adaptive Dynamic Treatment Regimes

Read the original on arXiv Machine Learning →

arXiv:2307. 12022v3 Announce Type: replace-cross Abstract: Optimizing individualized treatment sequences for patients who weigh multiple, competing outcomes differently poses a challenge for dynamic treatment regime (DTR) methods, which typically assume a single univariate outcome.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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