Peer-reviewedCC BY-NC-NDTranslational cancer research11 Aug 2026

Radiomics-based machine learning models decipher heterogeneity of anoikis-related molecular subtypes for prognostic stratification in head and neck squamous cell carcinoma

Linyong Wu¹
Dayou Wei¹
Wubiao Chen²
Songhua Li¹
Zhendong Lu²
Youwen Fu²
Wenci Liu²

¹Department of Medical Ultrasound , Maoming People’s Hospital , Maoming , ;
²Radiology Imaging Center , The Affiliated Hospital of Guangdong Medical University , Zhanjiang ,

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Cite

BibTeX

@article{wu2026radiomicsbased,
  title = {{Radiomics-based machine learning models decipher heterogeneity of anoikis-related molecular subtypes for prognostic stratification in head and neck squamous cell carcinoma}},
  author = {Linyong Wu and Dayou Wei and Wubiao Chen and Songhua Li and Zhendong Lu and Youwen Fu and Wenci Liu},
  journal = {Translational cancer research},
  year = {2026},
  month = aug,
  url = {https://europepmc.org/article/PMC/PMC13657819},
  note = {CC BY-NC-ND},
}

RIS

TY  - JOUR
TI  - Radiomics-based machine learning models decipher heterogeneity of anoikis-related molecular subtypes for prognostic stratification in head and neck squamous cell carcinoma
AU  - Linyong Wu
AU  - Dayou Wei
AU  - Wubiao Chen
AU  - Songhua Li
AU  - Zhendong Lu
AU  - Youwen Fu
AU  - Wenci Liu
PY  - 2026
DA  - 2026/08/11
JO  - Translational cancer research
UR  - https://europepmc.org/article/PMC/PMC13657819
SN  - 2218-676X
ER  -

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