This study presents a counterfactual inference approach for ordinary differential equations (ODEs) models. The methodology is applied to a model describing blood glucose regulation to assess the effects of personalized physical activity plans on type 2 diabetes progression. The analysis demonstrates how responses to physical activity vary among individuals based on β-cells mass and insulin sensitivity, resulting in diverse sets of counterfactual physical activity plans. This approach can eventually help identify individuals who might benefit from early diabetes prevention measures via personalized physical activity plans.

Counterfactual Inference Using Ordinary Differential Equations to Assess the Effect of Physical Activity on Type 2 Diabetes Onset

Lenatti M.
Primo
;
De Paola P. F.;Mongelli M.;Paglialonga A.
Penultimo
;
2025

Abstract

This study presents a counterfactual inference approach for ordinary differential equations (ODEs) models. The methodology is applied to a model describing blood glucose regulation to assess the effects of personalized physical activity plans on type 2 diabetes progression. The analysis demonstrates how responses to physical activity vary among individuals based on β-cells mass and insulin sensitivity, resulting in diverse sets of counterfactual physical activity plans. This approach can eventually help identify individuals who might benefit from early diabetes prevention measures via personalized physical activity plans.
2025
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
9783031958373
9783031958380
Counterfactual inference
ODEs
Personalized treatment
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/551865
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