Radiomics and dosiomics signature from whole lung predicts radiation pneumonitis: A model development study with prospective external validation and decision-curve analysis

Z. Zhang; Z. Wang; A. Dekker; L. Wee

doi:10.1016/j.annonc.2022.02.120

Radiomics and dosiomics signature from whole lung predicts radiation pneumonitis: A model development study with prospective external validation and decision-curve analysis

Research output: Contribution to journal › Conference Abstract/Poster in journal › Academic

Original language	English
Pages (from-to)	S119-S119
Number of pages	1
Journal	Annals of Oncology
Volume	33
DOIs	https://doi.org/10.1016/j.annonc.2022.02.120
Publication status	Published - 1 Apr 2022

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Cite this

@article{8203807f6e524502a12802ba5cc8d563,

title = "Radiomics and dosiomics signature from whole lung predicts radiation pneumonitis: A model development study with prospective external validation and decision-curve analysis",

author = "Z. Zhang and Z. Wang and A. Dekker and L. Wee",

year = "2022",

month = apr,

day = "1",

doi = "10.1016/j.annonc.2022.02.120",

language = "English",

volume = "33",

pages = "S119--S119",

journal = "Annals of Oncology",

issn = "0923-7534",

publisher = "Oxford University Press",

}

TY - JOUR

T1 - Radiomics and dosiomics signature from whole lung predicts radiation pneumonitis: A model development study with prospective external validation and decision-curve analysis

AU - Zhang, Z.

AU - Wang, Z.

AU - Dekker, A.

AU - Wee, L.

PY - 2022/4/1

Y1 - 2022/4/1

U2 - 10.1016/j.annonc.2022.02.120

DO - 10.1016/j.annonc.2022.02.120

M3 - Conference Abstract/Poster in journal

SN - 0923-7534

VL - 33

SP - S119-S119

JO - Annals of Oncology

JF - Annals of Oncology

ER -