A Hybrid Machine Learning CT-Based Radiomics Nomogram for Predicting Cancer-Specific Survival in Curatively Resected Colorectal Cancer.

Journal: Academic radiology
PMID: 39922745

Abstract

RATIONALE AND OBJECTIVES: To develop and validate a computed tomography-based radiomics nomogram for cancer-specific survival (CSS) prediction in curatively resected colorectal cancer (CRC), and its performance was compared with the American Joint Committee on Cancer (AJCC) staging and clinical-pathological models.

Authors

  • Tingting Hong
    Department of Medical Oncology, the Affiliated Hospital of Jiangnan University, No.1000, Hefeng Road, Wuxi 214000, China (T.H., Y.M.). Electronic address: 553273569@qq.com.
  • Heng Zhang
    Department of Gastroenterology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Qiming Zhao
  • Li Liu
    Metanotitia Inc., Shenzhen, China.
  • Jun Sun
    School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu Province, PR China.
  • Shudong Hu
    Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, PR China.
  • Yong Mao
    State Key Laboratory of Large Yellow Croaker Breeding, Ningde Fufa Fisheries Company Limited, Ningde, 352000, China.

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