Machine learning-based radiomics for predicting outcomes in cervical cancer patients undergoing concurrent chemoradiotherapy.

Journal: Computers in biology and medicine
PMID: 38801795

Abstract

PURPOSES: To investigate the value of machine learning-based radiomics for predicting disease-free survival (DFS) and overall survival (OS) undergoing concurrent chemoradiotherapy (CCRT) for patients with locally advanced cervical cancer (LACC).

Authors

  • Wang Xin
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
  • Su Rixin
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
  • Li Linrui
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
  • Qin Zhihui
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
  • Liu Long
    Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Zhejiang University, Hangzhou, 310000, Zhejiang, China. Electronic address: liulong6179@163.com.
  • Zhang Yu
    Institute of Biomechanics and Medical Engineering, Department of Engineering Mechanics, Tsinghua University, 100084, Beijing, China.

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