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Synapse
April 13, 20260 citationsOpen Access

Epsilon-entropy in preclinical elements of syntropic clusters from tables of personalized diagnostics and prognosis

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VRValeriy Revo

Key Points

  • This study addresses how to recognize preclinical diseases in personalized syntropic clusters to enhance disease management.
  • Calculation of epsilon-entropy for preclinical disease forms.
  • Analysis of disease progression in personalized diagnostics.
  • Identification of stopped, slowed, or soon-to-manifest diseases.
  • Successfully identified preclinical diseases that have ceased development.
  • Noted preclinical diseases ready to manifest clinically in the near future.
  • Facilitated potential secondary prevention strategies without the need for therapeutic agents.

Abstract

In this work, the author, for the first time, enables physicians to gain knowledge about developing diseases that are in the preclinical stage in the syntropic cluster of each person. This will, for the first time, give physicians the opportunity to manage diseases and ensure secondary prevention, where there will be no therapeutic agents necessary for one disease, but contraindicated for others 1. Calculating the epsilon-entropy of these forms of disease will, for the first time, allow us to identify among preclinical diseases those that have either stopped or slowed down in their development, or, conversely, to identify those that are ready to manifest clinically in the near future.

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Cite This Study

Valeriy Revo (2026) studied this question.

synapsesocial.com/papers/69dc89473afacbeac03eb135https://doi.org/10.5281/zenodo.19520710
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  5. 5EZ Entropy: a software application for the entropy analysis of physiological time-series2019 · 21 citations