TY - JOUR
T1 - Dynamic Digital Twin
T2 - Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course
AU - Mulder, Skander Tahar
AU - Omidvari, Amir-Houshang
AU - Rueten-Budde, Anja J.
AU - Hai, Rihan
AU - Akgün, Can
AU - Tax, David M.J.
AU - Reinders, M.J.T.
AU - Reinders, Marcel
AU - Visch, Valentijn
AU - More Authors, null
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - artifical intelligence
KW - cardiovascular
KW - digital health
KW - digital twin
KW - disease
KW - health
KW - machine learning
KW - obstetrics
UR - http://www.scopus.com/inward/record.url?scp=85138444816&partnerID=8YFLogxK
U2 - 10.2196/35675
DO - 10.2196/35675
M3 - Article
C2 - 36103220
AN - SCOPUS:85138444816
SN - 1438-8871
VL - 24
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
IS - 9
M1 - e35675
ER -