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Synapse
January 20, 20260 citationsOpen Access

IHEP Recursive Loop Closure

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JJJason M JarmaczTLTrade Momentum LLC

Key Points

  • This research aims to establish a mechanism for continuous improvement of AI interventions based on patient data.
  • Specified the Recursive Loop Closure mechanism
  • Outlined the integration of AI-driven interventions
  • Described the digital twin framework
  • Identified the feedback process using clinical and behavioral data
  • Created a feedback system that improves AI interventions
  • Refined the digital twin framework based on real-world data
  • Enhanced patient outcome predictions and interventions

Abstract

This document specifies the Recursive Loop Closure (RLC) mechanism that bridges the gap between IHEP's AI-driven interventions and real-world patient outcomes, creating a morphogenetic feedback system that continuously refines the digital twin framework based on actual clinical and behavioral data.

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Cite This Study

Jarmacz et al. (2025) studied this question.

synapsesocial.com/papers/696f1a239e64f732b51ee6b9https://doi.org/10.5281/zenodo.18288171
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