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Dynamic Personalized Optimization: An AI Functionality Framework for Digital Therapeutics.

Dohyoung Rim1

  • 1Rowan Corporation, 18F Yonsei Severance Bld, 10, Tongil-ro, Jung-gu, Seoul, 04527, Republic of Korea, 82 2-6731-0810, 82 2-6930-5606.

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Summary
This summary is machine-generated.

Dynamic Personalized Optimization (DPO) offers a framework for artificial intelligence (AI) in digital therapeutics (DTx). It enables real-time, personalized treatments by continuously refining strategies based on patient data and AI models.

Keywords:
AI functionality frameworkdigital therapeuticsdynamic personalized optimizationlarge language modelspersonalized treatment

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Area of Science:

  • Digital Therapeutics
  • Artificial Intelligence
  • Personalized Medicine

Background:

  • Current digital therapeutics (DTx) face limitations in real-time personalization.
  • There is a need for adaptive treatment strategies in digital health interventions.

Purpose of the Study:

  • Introduce Dynamic Personalized Optimization (DPO) as a conceptual framework for AI in DTx.
  • Define core AI functions for real-time, personalized, and optimized treatment delivery.
  • Explore the role of large language models (LLMs) in supporting DPO.

Main Methods:

  • DPO integrates patient data, treatment content, usage feedback, and status measurements.
  • Predictive AI models are used to adapt treatment approaches based on patient responses.
  • LLMs are explored for processing diverse and complex data formats within the DPO framework.

Main Results:

  • DPO provides a structured, AI-driven approach to personalized digital interventions.
  • The framework facilitates continuous refinement of therapeutic strategies.
  • Potential for enhanced treatment efficacy and patient engagement through real-time adaptation.

Conclusions:

  • DPO establishes a robust framework for AI-driven personalization in DTx.
  • Integrating LLMs can enhance DPO's capability to handle complex patient data.
  • The DPO framework holds promise for improving the effectiveness of digital therapeutics.