Bayesian personalized dose constraints in selecting patients with non-small cell lung cancer for cardiac risk-adaptive treatment.

Chen M, Xu T, Xu T, Maguire RC, Chen X, Koutroumpakis E, Deswal A, Ajdari A, Niedzielski JS, Yang J, Meng QH, Mohan R, Lin R, Zhang X, Liao Z

Open source

DOI
10.1016/j.radonc.2026.111775
Published
2026 Sep 12
Container
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1016/j.radonc.2026.111775,
  title = {Bayesian personalized dose constraints in selecting patients with non-small cell lung cancer for cardiac risk-adaptive treatment.},
  author = {Chen M and Xu T and Xu T and Maguire RC and Chen X and Koutroumpakis E and Deswal A and Ajdari A and Niedzielski JS and Yang J and Meng QH and Mohan R and Lin R and Zhang X and Liao Z},
  year = {2026},
  journal = {Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology},
  doi = {10.1016/j.radonc.2026.111775},
  url = {https://doi.org/10.1016/j.radonc.2026.111775}
}

RIS

TY  - JOUR
TI  - Bayesian personalized dose constraints in selecting patients with non-small cell lung cancer for cardiac risk-adaptive treatment.
AU  - Chen M
AU  - Xu T
AU  - Xu T
AU  - Maguire RC
AU  - Chen X
AU  - Koutroumpakis E
AU  - Deswal A
AU  - Ajdari A
AU  - Niedzielski JS
AU  - Yang J
AU  - Meng QH
AU  - Mohan R
AU  - Lin R
AU  - Zhang X
AU  - Liao Z
PY  - 2026
JO  - Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
DO  - 10.1016/j.radonc.2026.111775
UR  - https://doi.org/10.1016/j.radonc.2026.111775
ER  - 

APA

M, C., T, X., T, X., RC, M., X, C., E, K., A, D., A, A., JS, N., J, Y., QH, M., R, M., R, L., X, Z., & Z, L. (2026). Bayesian personalized dose constraints in selecting patients with non-small cell lung cancer for cardiac risk-adaptive treatment.. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology. https://doi.org/10.1016/j.radonc.2026.111775

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