Application of Neural Networks to the Prediction of Lymph Node Metastasis in Oral Cancer

Toshiyuki Kawazu, Kazuyuki Araki, Kazunori Yoshiura, Eiji Nakayama, Shigenobu Kanda

研究成果: ジャーナルへの寄稿学術誌査読

8 被引用数 (Scopus)

抄録

Neural networks are a new type of computing algorithm. They are especially useful in pattern recognition. In this study we applied neural networks to the prediction of lymph node metastasis of patients with oral cancer. A data set of 1,116 lymph nodes verified histopathologically was used to train and evaluate the neural networks. Various three-layer feed-forward networks with a back-propagation algorithm were employed in this study. Performance of the neural networks was compared with that of radiologists and discriminant analysis (Quantification theory type II). Neural networks had a sensitivity of 80.6% and a specificity of 94.6%. Diagnostic accuracy of the neural networks was 93.6%, which was comparable to those of discriminant analysis and clinical radiologists.

本文言語英語
ページ(範囲)137-142
ページ数6
ジャーナルOral Radiology
19
2
DOI
出版ステータス出版済み - 1月 1 2003

!!!All Science Journal Classification (ASJC) codes

  • 歯科学(その他)
  • 放射線学、核医学およびイメージング

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