Retracted: Deep Learning-Based Glaucoma Detection Using CNN and Digital Fundus Images: A Promising Approach for Precise Diagnosis

Title:Retracted: Deep Learning-Based Glaucoma Detection Using CNN and Digital Fundus Images: A Promising Approach for Precise Diagnosis

Volume: 20

Author(s): Ruiying Song, Hong Wang and Yinghua Xing*

Affiliation:

• Department of Medical Insurance, Yantai Yuhuangding Hospital, No. 20, Yuhuangding Dong Road, Zhifu District, Yantai City, Shandong Province 264000, China

Abstract: The article entitled “Deep Learning-Basedd Glaucoma Detection Using CNN and Digital Fundus Images: A Promising Approach for Precise Diagnosis,” published in Current Medical Imaging, Volume 20, 2024 (https://bentham science.com/article/137214), has been retracted at the request of the authors. The decision to retract the article was made in accordance with the need for substantial revisions aimed at improving the clarity, coherence, and scientific rigor of the findings. The authors plan to restructure sections of the manuscript to better align them for the presentation of the methodology, results, and discussion.

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Cite this article as:

Song Ruiying, Wang Hong and Xing Yinghua*, Retracted: Deep Learning-Based Glaucoma Detection Using CNN and Digital Fundus Images: A Promising Approach for Precise Diagnosis, Current Medical Imaging 2024; 20 : e15734056257657 . https://dx.doi.org/10.2174/0115734056257657231115051020