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ID 115190
著者
長澤, 利彦 Saneikai Tsukazaki Hospital
Tabuchi, Hitoshi Saneikai Tsukazaki Hospital
Masumoto, Hiroki Saneikai Tsukazaki Hospital
Enno, Hiroki Rist Inc.
Ohara, Zaigen Saneikai Tsukazaki Hospital
Yoshizumi, Yuki Saneikai Tsukazaki Hospital
Ohsugi, Hideharu Saneikai Tsukazaki Hospital
キーワード
Ultrawide-field fundus ophthalmoscopy
Proliferative diabetic retinopathy
Deep learning
Deep convolutional neural network
資料タイプ
学術雑誌論文
抄録
Purpose
We investigated using ultrawide-field fundus images with a deep convolutional neural network (DCNN), which is a machine learning technology, to detect treatment-naïve proliferative diabetic retinopathy (PDR).
Methods
We conducted training with the DCNN using 378 photographic images (132 PDR and 246 non-PDR) and constructed a deep learning model. The area under the curve (AUC), sensitivity, and specificity were examined.
Result
The constructed deep learning model demonstrated a high sensitivity of 94.7% and a high specificity of 97.2%, with an AUC of 0.969.
Conclusion
Our findings suggested that PDR could be diagnosed using wide-angle camera images and deep learning.
掲載誌名
International Ophthalmology
ISSN
15732630
cat書誌ID
AA00234448
出版者
Springer Nature
39
10
開始ページ
2153
終了ページ
2159
発行日
2019-02-23
権利情報
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
医学系