Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation

• Main Authors: Eric A. Stahlberg (Author), Mohamed Abdel-Rahman (Author), Boris Aguilar (Author), Alireza Asadpoure (Author), Robert A. Beckman (Author), Lynn L. Borkon (Author), Jeffrey N. Bryan (Author), Colleen M. Cebulla (Author), Young Hwan Chang (Author), Ansu Chatterjee (Author), Jun Deng (Author), Sepideh Dolatshahi (Author), Olivier Gevaert (Author), Emily J. Greenspan (Author), Wenrui Hao (Author), Tina Hernandez-Boussard (Author), Pamela R. Jackson (Author), Marieke Kuijjer (Author), Adrian Lee (Author), Paul Macklin (Author), Subha Madhavan (Author), Matthew D. McCoy (Author), Navid Mohammad Mirzaei (Author), Talayeh Razzaghi (Author), Heber L. Rocha (Author), Leili Shahriyari (Author), Ilya Shmulevich (Author), Daniel G. Stover (Author), Yi Sun (Author), Tanveer Syeda-Mahmood (Author), Jinhua Wang (Author), Qi Wang (Author), Ioannis Zervantonakis (Author)
• Format: Book
• Published: Frontiers Media S.A., 2022-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoi...