Human Digital Twin for Personalized Elderly Type 2 Diabetes Management

Thamotharan, P and Srinivasan , S and Kesavadev, J and Krishnan, G and Mohan, V and Seshadhri, S and Bekiroglu, K and Toffanin, C (2023) Human Digital Twin for Personalized Elderly Type 2 Diabetes Management. Journal of Clinical Medicine, 12 (6). p. 1.

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Abstract

anaging Elderly type 2 diabetes (E-T2D) is challenging due to geriatric conditions (e.g., co-morbidity, multiple drug intake, etc.), and personalization becomes paramount for precision medicine. This paper presents a human digital twin (HDT) framework to manage E-T2D that exploits various patient-specific data and builds a suite of models exploiting the data for prediction and management to personalize diabetes treatment in E-T2D patients. These models include mathematical and deep-learning ones that capture different patient aspects. Consequently, the HDT virtualizes the patient from different viewpoints using an HDT that mimics the patient and has interfaces to update the virtual models simultaneously from measurements. Using these models the HDT obtains deeper insights about the patient. Further, an adaptive patient model fusing this information and a learning-based model predictive control (LB-MPC) algorithm are proposed. The geriatric conditions are captured as model parameters and constraints while solving the LB-MPC to personalize the insulin infusion for E-T2D management. The HDT is deployed on and illustrated with 15 patients using clinical trials and simulations. Our results show that HDT helps improve the time-in-range from 3–75% to 86–97% and reduces insulin infusion by 14–29%.

Item Type:Article
Official URL/DOI:https://www.mdpi.com/2077-0383/12/6/2094
Uncontrolled Keywords:Elderly type 2 diabetes (E-T2D); internet of medical things (IoMT); digital twin (DT); human digital twin (HDT); learning-based model predictive control (LB-MPC); personalization; precision medicine
Subjects:Diabetes Epidemiology
Divisions:Department of Diabetology
ID Code:1342
Deposited By:surendar radha
Deposited On:25 Mar 2023 12:27
Last Modified:25 Mar 2023 12:27

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