Research on imbalance machine learning methods for MRWI soft tissue sarcoma data.

Journal: BMC medical imaging
Published Date: Aug 26, 2022

Abstract

BACKGROUND: Soft tissue sarcoma is a rare and highly heterogeneous tumor in clinical practice. Pathological grading of the soft tissue sarcoma is a key factor in patient prognosis and treatment planning while the clinical data of soft tissue sarcoma are imbalanced. In this paper, we propose an effective solution to find the optimal imbalance machine learning model for predicting the classification of soft tissue sarcoma data.

Authors

  • Xuanxuan Liu
    College of Computer Science and Technology, Qingdao University, Qingdao, 266071 China.
  • Li Guo
    Department of Dental Implantology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
  • Hexiang Wang
    Department of Radiology, The Affiliated Hospital of Qingdao University, Shinan Jiangsu 16 Rd, Qingdao, Shandong 266003, China.
  • Jia Guo
    Department of Radiology, Stanford University, Stanford, CA, USA.
  • Shifeng Yang
    Department of Radiology, Shandong Provincial Hospital affiliated to Shandong University, Shandong University, Jinan, Shandong, P.R. China.
  • Lisha Duan
    Department of Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang, 050051, Hebei, China.

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