Diagnosis of Early Glottic Cancer Using Laryngeal Image and Voice Based on Ensemble Learning of Convolutional Neural Network Classifiers.

Journal: Journal of voice : official journal of the Voice Foundation
PMID: 36075802

Abstract

OBJECTIVES: The purpose of study is to improve the classification accuracy by comparing the results obtained by applying decision tree ensemble learning, which is one of the methods to increase the classification accuracy for a relatively small dataset, with the results obtained by the convolutional neural network (CNN) algorithm for the diagnosis of glottal cancer.

Authors

  • Ickhwan Kwon
    Department of Applied IT and Engineering, Pusan National University, Miryang, Gyeongsangnam-do, South Korea.
  • Soo-Geun Wang
    Department of Otorhinolaryngology-Head and Neck Surgery, College of Medicine, Pusan National University and Medical Research Institute, Pusan National University Hospital, Busan, South Korea.
  • Sung-Chan Shin
    Department of Otorhinolaryngology-Head and Neck Surgery, College of Medicine, Pusan National University and Medical Research Institute, Pusan National University Hospital, Busan, South Korea.
  • Yong-Il Cheon
    Department of Otorhinolaryngology-Head and Neck Surgery, College of Medicine, Pusan National University and Medical Research Institute, Pusan National University Hospital, Busan, South Korea.
  • Byung-Joo Lee
    Department of Otorhinolaryngology-Head and Neck Surgery, Pusan National University School of Medicine, Pusan National University and Biomedical Research Institute, Pusan National University Hospital, 1-10 Ami-Dong, Seo-Gu, Busan, 602-739, Korea. voiceleebj@gmail.com.
  • Jin-Choon Lee
    Department of Otorhinolaryngology-Head and Neck Surgery, Pusan National University Yangsan Hospital, Yangsan, Gyeongsangnam-do, South Korea.
  • Dong-Won Lim
    Department of Otorhinolaryngology-Head and Neck Surgery, Pusan National University Hospital, Busan, South Korea.
  • Cheolwoo Jo
    School of Electrical, Electronics & Control Engineering, Changwon National University, Changwon, South Korea.
  • Youngseuk Cho
    Department of Statistics, College of Natural Sciences, Pusan National University, Busan, South Korea.
  • Bum-Joo Shin
    Department of Applied IT and Engineering, Pusan National University, Miryang, Gyeongsangnam-do, South Korea. Electronic address: voicebjshin@gmail.com.

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