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

Clinical Information and Decision Making (1915) Innovations and Technology in Cancer Care (531)

Published on in Vol 24, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29455, first published .
Optimal Treatment Selection in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: Deep Q-Learning With a Patient-Physician Digital Twin Dyad

Optimal Treatment Selection in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: Deep Q-Learning With a Patient-Physician Digital Twin Dyad

Optimal Treatment Selection in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: Deep Q-Learning With a Patient-Physician Digital Twin Dyad

Authors of this article:

Elisa Tardini1, 2 Author Orcid Image ;   Xinhua Zhang1 Author Orcid Image ;   Guadalupe Canahuate3 Author Orcid Image ;   Andrew Wentzel1 Author Orcid Image ;   Abdallah S R Mohamed4, 5 Author Orcid Image ;   Lisanne Van Dijk4 Author Orcid Image ;   Clifton D Fuller4, 5 Author Orcid Image ;   G Elisabeta Marai1 Author Orcid Image
Article Authors Cited by (29) Tweetations (5) Metrics

Journals

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  14. Wentzel A, Attia S, Zhang X, Canahuate G, Fuller C, Marai G. DITTO: A Visual Digital Twin for Interventions and Temporal Treatment Outcomes in Head and Neck Cancer. IEEE Transactions on Visualization and Computer Graphics 2025;31(1):65 View
  15. Gaffinet B, Al Haj Ali J, Naudet Y, Panetto H. Human Digital Twins: A systematic literature review and concept disambiguation for industry 5.0. Computers in Industry 2025;166:104230 View
  16. Li X, Chang J, Venkatesan M, Wang Z, Moore J. Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modeling. BioData Mining 2025;18(1) View
  17. Xames M, Topcu T. How Can Digital Twins Support the Economic, Environmental, and Social Sustainability of Healthcare Systems: A Systematic Review Focused on the Triple Bottom Line. IEEE Access 2025;13:64390 View
  18. John A, Alhajj R, Rokne J. A systematic review of AI as a digital twin for prostate cancer care. Computer Methods and Programs in Biomedicine 2025;268:108804 View
  19. Frommeyer T, Gilbert M, Fursmidt R, Park Y, Khouzam J, Brittain G, Frommeyer D, Bett E, Bihl T. Reinforcement Learning and Its Clinical Applications Within Healthcare: A Systematic Review of Precision Medicine and Dynamic Treatment Regimes. Healthcare 2025;13(14):1752 View
  20. Sasitharasarma S, Alani N, Wisker Z. Is the Healthcare Industry Ready for Digital Twins? Examining the Opportunities and Challenges. Future Internet 2025;17(9):386 View
  21. Takada T, Tambas M, Clementel E, Leeuwenberg A, Sharabiani M, Damen J, Dunias Z, Nauta J, Idema D, Choi J, Meijerink L, Langendijk J, Moons K, Schuit E. Prognostic models for radiation-induced complications after radiotherapy in head and neck cancer patients. Cochrane Database of Systematic Reviews 2025;2025(9) View
  22. Tudor B, Shargo R, Gray G, Fierstein J, Kuo F, Burton R, Johnson J, Scully B, Asante-Korang A, Rehman M, Ahumada L. A scoping review of human digital twins in healthcare applications and usage patterns. npj Digital Medicine 2025;8(1) View
  23. Huang Q, Zeng W, Liu J, Zhang Z, Deng J, Qiu Z, Xu L, Wei Z, Lu Q, Gong L, Shi C, Zhong X. Shaping the future of nuclear reactors with digital twins: Current developments and perspectives. Applied Energy 2025;402:126922 View
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Books/Policy Documents

  1. Singh L, Kamra L. Information and Software Technologies. View
  2. Subasi A, Subasi M. Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry. View
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