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Condensed precision research protocol for ME/CFS

  • Collected some longitudinal data.
  • Machine learning techniques development is underway.

STUDY HYPOTHESIS AND DESCRIPTION

A condensed personalized research protocol would be the minimum number of samples from specific conditions that can accurately develop a biological signature unique to an individual with ME/CFS that can be used predict the improvement or worsening of their symptoms.

This protocol would be useful for tracking the development of ME/CFS, provide an understanding of the biology of the disease process in the individual, stratify ME/CFS individuals into biologically-defined subsets, test the efficacy of treatments, and monitor outcomes in clinical treatment trials.

 

OBJECTIVES

  1. Establish a condensed personalized research protocol that can be used to characterize ME/CFS in individual patients as it pertains their biological aspects of their self and a complex chronic disease.
  2. Integrate and analyze the data from metabolic longitudinal studies.
  3. Randomly sample each participants longitudinal data and analyze if a similar pattern can be observed with less data points.
  4. Develop an algorithm to recognize individual signatures and compare them across patients to identify patterns that can then reduce the length of the personalized research method.
  5. Test and validate algorithm on combined datasets bootstrapping.
  6. Retest tool by retesting a number of ME/CFS patients to determine if signature produced is consistent with the past.
Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME / CFS) Post Treatment Lyme Disease Syndrome (PTLDS), Fibromyalgia Leading Research. Delivering Hope.Open Medicine Foundation®

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