Estimating patient-specific organ doses from head and abdominal CT scans via machine learning with optimized regulation strength and feature quantity.

Journal: Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
PMID: 40112700

Abstract

PURPOSE: This study aims to investigate estimation of patient-specific organ doses from CT scans via radiomics feature-based SVR models with training parameter optimization, and maximize SVR models' predictive accuracy and robustness via fine-tuning regularization parameter and input feature quantities.

Authors

  • Wencheng Shao
    Institute of Radiation Medicine, Fudan University, Shanghai, China.
  • Liangyong Qu
    Department of Radiology, Shanghai Zhongye Hospital, Shanghai, China.
  • Xin Lin
    Department of Clinical Nutrition, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, 400042, China.
  • Weikang Yun
    Department of Radiation Physics, Harbin Medical University Cancer Hospital, Harbin, China.
  • Ying Huang
    Department of Otolaryngology, Head and Neck Surgery, Affiliated Hospital of Southwest Medical University Luzhou, Sichuan, China.
  • Weihai Zhuo
    Key Lab of Nuclear Physics & Ion-Beam Application (MOE), 12478Fudan University, Shanghai, China.
  • Haikuan Liu
    Institute of Radiation Medicine, Fudan University, Shanghai, China.

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