From Linear-quadratic to Machine Learning in Radiobiological Modeling for Radiotherapy Planning: Resolving the Complexity-Utility Paradox with Hybrid Physics-informed Neural Networks.
- DOI
- 10.4103/jmp.jmp_105_26
- Published
- 2026 Jul-Sep
- Container
- Journal of medical physics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.4103/jmp.jmp_105_26,
title = {From Linear-quadratic to Machine Learning in Radiobiological Modeling for Radiotherapy Planning: Resolving the Complexity-Utility Paradox with Hybrid Physics-informed Neural Networks.},
author = {Mondal K and Vijay A and Mandal A and Patel G},
year = {2026},
journal = {Journal of medical physics},
doi = {10.4103/jmp.jmp_105_26},
url = {https://doi.org/10.4103/jmp.jmp_105_26}
}RIS
TY - JOUR TI - From Linear-quadratic to Machine Learning in Radiobiological Modeling for Radiotherapy Planning: Resolving the Complexity-Utility Paradox with Hybrid Physics-informed Neural Networks. AU - Mondal K AU - Vijay A AU - Mandal A AU - Patel G PY - 2026 JO - Journal of medical physics DO - 10.4103/jmp.jmp_105_26 UR - https://doi.org/10.4103/jmp.jmp_105_26 ER -
APA
K, M., A, V., A, M., & G, P. (2026). From Linear-quadratic to Machine Learning in Radiobiological Modeling for Radiotherapy Planning: Resolving the Complexity-Utility Paradox with Hybrid Physics-informed Neural Networks.. Journal of medical physics. https://doi.org/10.4103/jmp.jmp_105_26
Source records
- pubmed · retrieved 2026-11-10T10:23:58.258Z