Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis.

Journal: European radiology
Published Date: Aug 1, 2020

Abstract

OBJECTIVES: To assess the diagnostic accuracy of machine learning (ML) in predicting isocitrate dehydrogenase (IDH) mutations in patients with glioma and to identify potential covariates that could influence the diagnostic performance of ML.

Authors

  • Jing Zhao
    Department of Pharmacy, Pharmacoepidemiology and Drug Safety Research Group, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
  • Yingqian Huang
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.
  • Yukun Song
    Department of Radiology, The First Affiliated Hospital of Xiamen University, Xiamen, 361003, China.
  • Dingxiang Xie
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.
  • Manshi Hu
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.
  • Haishan Qiu
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.
  • Jianping Chu
    Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China. truechu@hotmail.com.

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