Integrated clinical-radiomic model for predicting treatment response of concurrent chemo-radiotherapy and radiotherapy alone in controversial subgroup of AJCC/UICC ninth edition stage I nasopharyngeal cancer

Integrating with clinical and radiomic features could provide prognostic information on 5-year PFS under either treatment regimen, guiding individualized decisions of chemotherapy based on the predicted treatment outcome.

Authors

Institutions

Publication Details

Journal
Chinese Journal of Cancer Research
Published
2025-01-01
DOI
https://doi.org/10.21147/j.issn.1000-9604.2025.02.01
Citations
4
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
5.44
Controls
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article

Integrated clinical-radiomic model for predicting treatment response of concurrent chemo-radiotherapy and radiotherapy alone in controversial subgroup of AJCC/UICC ninth edition stage I nasopharyngeal cancer

Lawrence Chan, Mohan Huang, Luoyi Kong, Xinyue Chen et al.
4 citations
Chinese Journal of Cancer Research
Radiomics and Machine Learning in Medical Imaging
5.44
article

Integrated clinical-radiomic model for predicting treatment response of concurrent chemo-radiotherapy and radiotherapy alone in controversial subgroup of AJCC/UICC ninth edition stage I nasopharyngeal cancer

Lawrence Chan, Mohan Huang, Luoyi Kong, Xinyue Chen, Ka Yan Ng, S Cheung
article en
4 citations

Abstract

Integrating with clinical and radiomic features could provide prognostic information on 5-year PFS under either treatment regimen, guiding individualized decisions of chemotherapy based on the predicted treatment outcome.

Chinese Journal of Cancer ResearchVol. 37(2)
Hong Kong Polytechnic University (HK), Tuen Mun Hospital (CN), Hong Kong Sanatorium and Hospital (HK)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Radiomics and Machine Learning in Medical Imaging
5.44
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