Automatic discrimination of Yamamoto-Kohama classification by machine learning approach for invasive pattern of oral squamous cell carcinoma using digital microscopic images: A retrospective study

The Yamamoto –Kohama criteria are clinically useful for determining the mode of tumor invasion, especially in Japan. However, this evaluation method is based on subjective visual findings and has led to significant differences in determinations between evaluators and facilities. In this retrospective study, we aimed to develop an automatic method of determining the mode of invasion based on the processing of digital medical images.

Source: Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontics - October 14, 2021 Category: ENT & OMF Authors: Kunio Yoshizawa, Hidetoshi Ando, Yujiro Kimura, Shuichi Kawashiri, Hiroshi Yokomichi, Akinori Moroi, Koichiro Ueki Source Type: research