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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

This feature enables health care professionals to get a relevant view of factors influencing disease and health conditions of a patient, which can guide actions to optimize health care pathways. Different prediction algorithms can be used to answer medical questions, and real-world personalized predictions can be updated to meet the dynamic circumstances of individuals and their medical history.

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 MJ Tax, Marcel Reinders, Eric Boersma, Dimitris Rizopoulos, Valentijn Visch, Régine Steegers-Theunissen

J Med Internet Res 2022;24(9):e35675