Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas
- DOI
- 10.3389/frai.2023.1222612
- Published
- 2023-10-11
- Container
- Frontiers in Artificial Intelligence
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/frai.2023.1222612,
title = {Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas},
author = {Anirban Chaudhuri and Graham Pash and David A. Hormuth and Guillermo Lorenzo and Michael Kapteyn and Chengyue Wu and Ernesto A. B. F. Lima and Thomas E. Yankeelov and Karen Willcox},
year = {2023},
journal = {Frontiers in Artificial Intelligence},
doi = {10.3389/frai.2023.1222612},
url = {https://doi.org/10.3389/frai.2023.1222612}
}RIS
TY - JOUR TI - Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas AU - Anirban Chaudhuri AU - Graham Pash AU - David A. Hormuth AU - Guillermo Lorenzo AU - Michael Kapteyn AU - Chengyue Wu AU - Ernesto A. B. F. Lima AU - Thomas E. Yankeelov AU - Karen Willcox PY - 2023 JO - Frontiers in Artificial Intelligence DO - 10.3389/frai.2023.1222612 UR - https://doi.org/10.3389/frai.2023.1222612 ER -
APA
Chaudhuri, A., Pash, G., Hormuth, D. A., Lorenzo, G., Kapteyn, M., Wu, C., Lima, E. A. B. F., Yankeelov, T. E., & Willcox, K. (2023). Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2023.1222612
Source records
- crossref · retrieved 2026-11-09T06:47:53.453Z