Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas.

Chaudhuri A, Pash G, Hormuth DA 2nd, Lorenzo G, Kapteyn M, Wu C, Lima EABF, Yankeelov TE, Willcox K

Open source

DOI
10.3389/frai.2023.1222612
Published
2023
Container
Frontiers in artificial intelligence
Publisher
Not recorded
Open access
yes

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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 = {Chaudhuri A and Pash G and Hormuth DA 2nd and Lorenzo G and Kapteyn M and Wu C and Lima EABF and Yankeelov TE and Willcox K},
  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  - Chaudhuri A
AU  - Pash G
AU  - Hormuth DA 2nd
AU  - Lorenzo G
AU  - Kapteyn M
AU  - Wu C
AU  - Lima EABF
AU  - Yankeelov TE
AU  - Willcox K
PY  - 2023
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2023.1222612
UR  - https://doi.org/10.3389/frai.2023.1222612
ER  - 

APA

A, C., G, P., 2nd, H. D., G, L., M, K., C, W., EABF, L., TE, Y., & K, W. (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

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