Prediction of the Ki-67 expression level in head and neck squamous cell carcinoma with machine learning-based multiparametric MRI radiomics: a multicenter study

Prediction of the Ki-67 expression level in head and neck squamous cell carcinoma with machine learning-based multiparametric MRI radiomics: a multicenter study

Abstract Background This study aimed to develop and validate a machine learning (ML)-based fusion model to preoperatively predict Ki-67 expression levels in patients with head and neck squamous cell carcinoma (HNSCC) using multiparametric magnetic resonance imaging (MRI). Methods A total of 351 pati...

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Bibliographic Details
Main Authors: Weiyue Chen, Guihan Lin, Yongjun Chen, Feng Cheng, Xia Li, Jiayi Ding, Yi Zhong, Chunli Kong, Minjiang Chen, Shuiwei Xia, Chenying Lu, Jiansong Ji
Format: Article
Language:English
Published: BMC 2024-04-01
Series:BMC Cancer
Subjects:
Head and neck squamous cell carcinoma
Magnetic resonance imaging
Machine learning
Radiomics
Online Access:https://doi.org/10.1186/s12885-024-12026-x

Internet

https://doi.org/10.1186/s12885-024-12026-x

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