Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.

Journal: Progress in orthodontics
PMID: 39279025

Abstract

OBJECTIVES: This study aimed to assess the accuracy of machine learning (ML) models with feature selection technique in classifying cervical vertebral maturation stages (CVMS). Consensus-based datasets were used for models training and evaluation for their model generalization capabilities on unseen datasets.

Authors

  • Potjanee Kanchanapiboon
    Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wang Lang Rd, Siriraj, Bangkok Noi, Bangkok, 10700, Thailand.
  • Pitipat Tunksook
    Department of Orthodontics, Faculty of Dentistry, Mahidol University, 6 Yothi Rd, Thung Phaya Thai, Ratchathewi, Bangkok, 10400, Thailand.
  • Prinya Tunksook
    Private Practice, Bangkok, Thailand.
  • Panrasee Ritthipravat
    Department of Biomedical Engineering, Faculty of Engineering, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, 73170, Nakhon Pathom, Thailand. panrasee.rit@mahidol.ac.th.
  • Supatchai Boonpratham
    Department of Orthodontics, Faculty of Dentistry, Mahidol University, 6 Yothi Rd, Thung Phaya Thai, Ratchathewi, Bangkok, 10400, Thailand.
  • Yodhathai Satravaha
    Department of Orthodontics, Faculty of Dentistry, Mahidol University, 6 Yothi Rd, Thung Phaya Thai, Ratchathewi, Bangkok, 10400, Thailand.
  • Chaiyapol Chaweewannakorn
    Department of Orthodontics, Faculty of Dentistry, Mahidol University, 6 Yothi Rd, Thung Phaya Thai, Ratchathewi, Bangkok, 10400, Thailand.
  • Supakit Peanchitlertkajorn
    Department of Orthodontics, Faculty of Dentistry, Mahidol University, 6 Yothi Rd, Thung Phaya Thai, Ratchathewi, Bangkok, 10400, Thailand. supakit.pea@mahidol.ac.th.

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