The Dynamic Digital Twin: diagnosis, treatment, prediction and prevention of disease during the life course (Preprint)

Autor: Skander Tahar Mulder, Amir-Houshang Omidvari, Anja,J. Rueten-Budde, Pei-Hua Huang, Ki-Hun Kim, Babette Bais, Melek Rousian, Rihan Hai, Can Akgun, Jeanine Roeters van Lennep, Sten Willemsen, Peter R Rijnbeek, David M.J. Tax, Marcel Reinders, Erik Boersma, Dimitris Rizopoulos, Valentijn Visch, Régine Steegers-Theunissen
Rok vydání: 2021
Popis: UNSTRUCTURED A Digital Twin (DT), which is defined originally as a virtual representation of a physical asset, system or process, is a new concept in healthcare. DT in healthcare cannot be a single technology, but a domain adapted multi-modal modelling approach, which incorporates the acquisition, management, analysis, prediction, and interpretation of the data, aiming to improve medical decision making. However, there are many challenges and barriers that has to be overcome before a DT can be used in healthcare. In this viewpoint paper, we address these challenges, and envision a dynamic DT in healthcare for optimizing individual patient health care journeys. 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, which guide the development of the dynamic DT and the implementation strategies in healthcare.
Databáze: OpenAIRE