ArticlePLoS computational biology2018
Personalizing physical exercise in a computational model of fuel homeostasis.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06195566 (Physics Informed Machine Learning-based Prediction and Reversion of Impaired Fasting Glucose Management), which is not on this map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Physics Informed Machine Learning-based Prediction and Reversion of Impaired Fasting Glucose Management
Who cites it
11 citing papers in PubMed.
- Data, Process, and Data-Driven Representations of Digital Twins in Diabetes: Scoping Review.JMIR diabetes · 2026Review
- Modeling ovarian hormone effects on glucose-insulin control in type 1 diabetes.Bioengineering & translational medicine · 2026Review
- Nonlinear, Multicomponent Physical Exercise With Heart Rate Variability-Guided Prescription in Women With Breast Cancer During Treatment: Feasibility and Preliminary Results (ATOPE Study).Physical therapy · 2023Article
- New model of glucose-insulin regulation characterizes effects of physical activity and facilitates personalized treatment evaluation in children and adults with type 1 diabetes.PLoS computational biology · 2023Article
- Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes.iScience · 2021Article
- Modelling glucose dynamics during moderate exercise in individuals with type 1 diabetes.PloS one · 2021Article
- Mathematical Model of Glucagon Kinetics for the Assessment of Insulin-Mediated Glucagon Inhibition During an Oral Glucose Tolerance Test.Frontiers in endocrinology · 2021Article
- Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices.BMC bioinformatics · 2020Article
- Systems View of Deconditioning During Spaceflight Simulation in the PlanHab Project: The Departure of UrineFrontiers in physiology · 2020Article
- Modeling the Effect of High Calorie Diet on the Interplay between Adipose Tissue, Inflammation, and Diabetes.Computational and mathematical methods in medicine · 2019Article
- A statistical virtual patient population for the glucoregulatory system in type 1 diabetes with integrated exercise model.PloS one · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The beneficial effects of physical activity for the prevention and management of several chronic diseases are widely recognized. Mathematical modeling of the effects of physical exercise in body metabolism and in particular its influence on the control of glucose homeostasis is of primary importance in the development of eHealth monitoring devices for a personalized medicine. Nonetheless, to date only a few mathematical models have been aiming at this specific purpose. We have developed a whole-body computational model of the effects on metabolic homeostasis of a bout of physical exercise. Built upon an existing model, it allows to detail better both subjects' characteristics and physical exercise, thus determining to a greater extent the dynamics of the hormones and the metabolites considered.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.