Comprehensive Potential of Artificial Intelligence for Predicting PD-L1 Expression and EGFR Mutations in Lung Cancer: A Systematic Review and Meta-Analysis.

Journal: Journal of computer assisted tomography
PMID: 39143665

Abstract

OBJECTIVE: To evaluate the methodological quality and the predictive performance of artificial intelligence (AI) for predicting programmed death ligand 1 (PD-L1) expression and epidermal growth factor receptors (EGFR) mutations in lung cancer (LC) based on systematic review and meta-analysis.

Authors

  • Linyong Wu
    Department of Medical Ultrasound, Maoming People's Hospital, Maoming, 525011, Guangdong, P. R. China.
  • Dayou Wei
    Department of Medical Ultrasound, Maoming People's Hospital, Maoming, 525011, Guangdong, P. R. China. weidayoumm@163.com.
  • Wubiao Chen
    Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China.
  • Chaojun Wu
    Department of Medical Ultrasound, Maoming People's Hospital, Maoming, 525011, Guangdong, P. R. China.
  • Zhendong Lu
    Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China.
  • Songhua Li
    Department of Medical Ultrasound, Maoming People's Hospital, Maoming, 525011, Guangdong, P. R. China.
  • Wenci Liu
    Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China.

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