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Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course.
Mulder, Skander Tahar; Omidvari, Amir-Houshang; Rueten-Budde, Anja J; Huang, Pei-Hua; Kim, Ki-Hun; Bais, Babette; Rousian, Melek; Hai, Rihan; Akgun, Can; van Lennep, Jeanine Roeters; Willemsen, Sten; Rijnbeek, Peter R; Tax, David Mj; Reinders, Marcel; Boersma, Eric; Rizopoulos, Dimitris; Visch, Valentijn; Steegers-Theunissen, Régine.
Afiliação
  • Mulder ST; Pattern Recognition Lab, Mathematics and Computer Science, Technical University Delft, Delft, Netherlands.
  • Omidvari AH; Department of Cardiology, Erasmus Medical Center, Rotterdam, Netherlands.
  • Rueten-Budde AJ; Department of Public Health, Erasmus Medical Center, Rotterdam, Netherlands.
  • Huang PH; Department of Biostatistics, Erasmus Medical Center, Rotterdam, Netherlands.
  • Kim KH; Department of Medical Ethics and Philosophy, Erasmus Medical Center, Rotterdam, Netherlands.
  • Bais B; Department of Industrial Engineering, Pusan National University, Busan, Republic of Korea.
  • Rousian M; Obstetrics and Gynaecology, Erasmus Medical Center, Rotterdam, Netherlands.
  • Hai R; Obstetrics and Gynaecology, Erasmus Medical Center, Rotterdam, Netherlands.
  • Akgun C; Web Information Systems Group, Mathematics and Computer Science, Technical University of Delft, Delft, Netherlands.
  • van Lennep JR; Web Information Systems Group, Mathematics and Computer Science, Technical University of Delft, Delft, Netherlands.
  • Willemsen S; Bioelectronics Section, Department of Microelectronics, Faculty of Electrical Engineering, Technical University Delft, Delft, Netherlands.
  • Rijnbeek PR; Department of Internal Medicine, Erasmus Medical Center, Rotterdam, Netherlands.
  • Tax DM; Department of Biostatistics, Erasmus Medical Center, Rotterdam, Netherlands.
  • Reinders M; Department of Medical Informatics, Erasmus Medical Center, Rotterdam, Netherlands.
  • Boersma E; Pattern Recognition Lab, Mathematics and Computer Science, Technical University Delft, Delft, Netherlands.
  • Rizopoulos D; Pattern Recognition Lab, Mathematics and Computer Science, Technical University Delft, Delft, Netherlands.
  • Visch V; Department of Cardiology, Erasmus Medical Center, Rotterdam, Netherlands.
  • Steegers-Theunissen R; Department of Biostatistics, Erasmus Medical Center, Rotterdam, Netherlands.
J Med Internet Res ; 24(9): e35675, 2022 09 14.
Article em En | MEDLINE | ID: mdl-36103220
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Assistência ao Paciente / Acontecimentos que Mudam a Vida Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Assistência ao Paciente / Acontecimentos que Mudam a Vida Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda