Machine Learning Analysis of Gaze Data for Enhanced Precision in Diagnosing Oral Mucosal Diseases

Uchida, Shuji; Hiraoka, Shin-Ichiro; Kawamura, Kohei et al.

Journal of Clinical Medicine, 2024, 13(1), 136

アクセス数:869件（2025-08-15 10:01 集計）

固定URL: https://hdl.handle.net/11094/93533

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タイトル
Machine Learning Analysis of Gaze Data for Enhanced Precision in Diagnosing Oral Mucosal Diseases
著者
著者名
Uchida, Shuji
NRID
1000070615616 1000070615616
researchmap permalink
shinichirohiraoka shinichirohiraoka
Scopus Author ID
8670641300 8670641300
著者名
Hiraoka, Shin-Ichiro
NRID
1000020880157 1000020880157
ORCID
0000-0002-2983-0943 0000-0002-2983-0943
researchmap permalink
koheikawamura koheikawamura
著者名
Kawamura, Kohei
著者名
Sakamoto, Katsuya
著者名
Akiyama, Ryo
NRID
1000000367541 1000000367541
ORCID
0000-0002-0306-3627 0000-0002-0306-3627
researchmap permalink
mes5 mes5
Scopus Author ID
56395750500 56395750500
著者名
Tanaka, Susumu
キーワード等
diagnostic algorithm
gaze data
heatmap analysis
intraoral photographs
oral mucosal diseases
support vector machines
visual examination
内容
Uchida S., Hiraoka S.I., Kawamura K., et al. Machine Learning Analysis of Gaze Data for Enhanced Precision in Diagnosing Oral Mucosal Diseases. Journal of Clinical Medicine 13, 136 (2024); https://doi.org/10.3390/jcm13010136.
抄録
The diagnosis of oral mucosal diseases is a significant challenge due to their diverse differential characteristics. Risk assessment of lesions by visual examination is a complex process due to the lack of definitive guidelines. This study aimed to improve this process by creating a diagnostic algorithm using gaze data acquired during oral mucosal disease examinations. A total of 78 dentists were included in this study. Tobii Pro Nano® (Tobii Technology) was used to acquire gaze data during clinical photographic visual examinations. Advanced analysis tools such as support vector machines and heatmaps were used to visualize the gazing tendencies of a group of skilled oral surgeons, focusing on the number of gazes per region and the gazing time ratios. The preliminary findings showed the possibility of visualizing gazing tendencies and identifying areas of importance for diagnosis. The classification of intraoral photographs based on gross features revealed the existence of an optimal examination method for each category and diagnostically significant areas. This novel approach to analyzing gaze data has the potential to refine diagnostic techniques and increase both accuracy and efficiency.
出版者
Multidisciplinary Digital Publishing Institute (MDPI)
収録物名
Journal of Clinical Medicine
巻(号)
13(1)
ページ
136
刊行年月
2024-01-01
言語
英語
ハンドルURL
https://hdl.handle.net/11094/93533
eISSN
20770383
関連情報 (isIdenticalTo)
DOI (出版社版)
https://doi.org/10.3390/jcm13010136
アクセス権
open access
権利情報
This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ
Version of Record
カテゴリ
学術雑誌論文 Journal Article