Dynamic Personalized Optimization Enables Real-Time Digital Therapeutics
Dohyoung Rim publishes in JMIR Medical Informatics (2026) a conceptual framework called Dynamic Personalized Optimization (DPO) defining AI functions for real-time personalized digital therapeutics. The paper formalizes four data types (user, status, content, feedback), proposes predictive-model approaches to optimize treatment content by predicting feedback or final patient status, and notes LLMs can help process heterogeneous inputs. The framework aims to improve engagement and therapeutic effectiveness.
Scoring Rationale
Peer-reviewed, actionable DTx personalization framework drives relevance; limitation is conceptual novelty rather than empirical validation.
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Sources
- Read OriginalDynamic Personalized Optimization: An AI Functionality Framework for Digital Therapeuticsmedinform.jmir.org
