Methodological quality of machine learning-based quantitative imaging analysis studies in esophageal cancer: a systematic review of clinical outcome prediction after concurrent chemoradiotherapy

Z.W. Shi*, Z. Zhang*, Z.Y. Liu, L.J. Zhao, Z.X. Ye, A. Dekker, L. Wee

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

Original languageEnglish
Number of pages20
JournalEuropean Journal of Nuclear Medicine and Molecular Imaging
DOIs
Publication statusE-pub ahead of print - 23 Dec 2021

Keywords

  • Quantitative imaging analysis
  • Radiomics
  • Esophageal cancer
  • Concurrent chemoradiotherapy
  • Clinical outcomes
  • Methodological assessment
  • PATHOLOGICAL COMPLETE RESPONSE
  • TEXTURE ANALYSIS
  • F-18-FDG PET
  • PREOPERATIVE CHEMORADIOTHERAPY
  • NEOADJUVANT CHEMORADIOTHERAPY
  • RADIATION PNEUMONITIS
  • GENETIC-VARIANTS
  • TUMOR RESPONSE
  • RADIOMICS
  • FEATURES

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