This paper is in the following e-collection/theme issue:

Viewpoints and Perspectives (514) Machine Learning (1465) Clinical Informatics (1022) Artificial Intelligence (1371) Clinical Information and Decision Making (1407)

Published on in Vol 24, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35675, first published .
Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course

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

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

Authors of this article:

Skander Tahar Mulder1 Author Orcid Image ;   Amir-Houshang Omidvari2, 3 Author Orcid Image ;   Anja J Rueten-Budde4 Author Orcid Image ;   Pei-Hua Huang5 Author Orcid Image ;   Ki-Hun Kim6 Author Orcid Image ;   Babette Bais7 Author Orcid Image ;   Melek Rousian7 Author Orcid Image ;   Rihan Hai8 Author Orcid Image ;   Can Akgun8, 9 Author Orcid Image ;   Jeanine Roeters van Lennep10 Author Orcid Image ;   Sten Willemsen4 Author Orcid Image ;   Peter R Rijnbeek11 Author Orcid Image ;   David MJ Tax1 Author Orcid Image ;   Marcel Reinders1 Author Orcid Image ;   Eric Boersma2 Author Orcid Image ;   Dimitris Rizopoulos4 Author Orcid Image ;   Valentijn Visch12 Author Orcid Image ;   Régine Steegers-Theunissen7 Author Orcid Image
Article Authors Cited by (13) Tweetations (8) Metrics

Journals

  1. Abeltino A, Bianchetti G, Serantoni C, Riente A, De Spirito M, Maulucci G. Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction. Nutrients 2023;15(5):1199 View
  2. Tourassi G. Computational medicine: Grand challenges and opportunities for revolutionizing personalized healthcare. Frontiers in Medical Engineering 2023;1 View
  3. Gazerani P. Intelligent Digital Twins for Personalized Migraine Care. Journal of Personalized Medicine 2023;13(8):1255 View
  4. Calcaterra V, Pagani V, Zuccotti G. Maternal and fetal health in the digital twin era. Frontiers in Pediatrics 2023;11 View
  5. Sheng B, Wang Z, Qiao Y, Xie S, Tao J, Duan C. Detecting latent topics and trends of digital twins in healthcare: A structural topic model-based systematic review. DIGITAL HEALTH 2023;9 View
  6. Erdős B, O’Donovan S, Adriaens M, Gijbels A, Trouwborst I, Jardon K, Goossens G, Afman L, Blaak E, van Riel N, Arts I. Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism. Scientific Reports 2024;14(1) View
  7. Vallée A. Envisioning the Future of Personalized Medicine: Role and Realities of Digital Twins. Journal of Medical Internet Research 2024;26:e50204 View
  8. Rayhana R, Bai L, Xiao G, Liao M, Liu Z. Digital Twin Models: Functions, Challenges, and Industry Applications. IEEE Journal of Radio Frequency Identification 2024;8:282 View
  9. Albertini J, Derycke L, Millon A, Soler R. Digital twin and artificial intelligence technologies for predictive planning of endovascular procedures. Seminars in Vascular Surgery 2024;37(3):306 View
  10. Tibrewala A, Itchhaporia D. Revolutionizing Hypertension Management in Type 2 Diabetes. JACC: Advances 2024;3(9):101173 View
  11. Aghaabbasi M, Sabri S. Potentials of digital twin system for analyzing travel behavior decisions. Travel Behaviour and Society 2025;38:100902 View

Books/Policy Documents

  1. Sathish A, Ranjan A, Mahek A. Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0. View