In this study, the results of 46170 simulations corresponding to the same number of virtual subjects, experiencing different lifestyle conditions, are analysed for the construction of a statistical model able to recapitulate the simulated dynamics.
Investigation about the mechanisms involved in the onset of type 2 diabetes in absence of familiarity is the focus of a research project which has led to the development of a computational model that recapitulates the aetiology of the disease. The model simulates the metabolic and immunological alterations related to type-2 diabetes associated to several clinical, physiological and behavioural characteristics of representative virtual patients.
Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices
Stolfi Paola;Palumbo Maria Concetta;Tieri Paolo;Castiglione Filippo
2019
Abstract
Investigation about the mechanisms involved in the onset of type 2 diabetes in absence of familiarity is the focus of a research project which has led to the development of a computational model that recapitulates the aetiology of the disease. The model simulates the metabolic and immunological alterations related to type-2 diabetes associated to several clinical, physiological and behavioural characteristics of representative virtual patients.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
