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Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course.

Authors :
Mulder, Skander Tahar
Omidvari, Amir-Houshang
Rueten-Budde, Anja J
Huang, Pei-Hua
Kim, Ki-Hun
Bais, Babette
Rousian, Melek
Hai, Rihan
Akgun, Can
Lennep, Jeanine Roeters van
Willemsen, Sten
Rijnbeek, Peter R
Tax, David MJ
Reinders, Marcel
Boersma, Eric
Rizopoulos, Dimitris
Visch, Valentijn
Steegers-Theunissen, Régine
van Lennep, Jeanine Roeters
Source :
Journal of Medical Internet Research; Sep2022, Vol. 24 Issue 9, pN.PAG-N.PAG, 1p
Publication Year :
2022

Abstract

A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to improve medical decision-making. However, there are many challenges and barriers that must be overcome before a DT can be used in health care. In this viewpoint paper, we build on the current literature, address these challenges, and describe a dynamic DT in health care for optimizing individual patient health care journeys, specifically for women at risk for cardiovascular complications in the preconception and pregnancy periods and across the life course. We describe how we can commit multiple domains to developing this DT. With our cross-domain definition of the DT, we aim to define future goals, trade-offs, and methods that will guide the development of the dynamic DT and implementation strategies in health care. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14394456
Volume :
24
Issue :
9
Database :
Supplemental Index
Journal :
Journal of Medical Internet Research
Publication Type :
Academic Journal
Accession number :
159528618
Full Text :
https://doi.org/10.2196/35675