Hybrid Model Structure for Diabetic Retinopathy Classification
Joint Authors
Cheng, Siyi
Liu, Hao
Sun, Jie
Yue, Keqiang
Pan, Chengming
Li, Wenjun
Source
Journal of Healthcare Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-13
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Diabetic retinopathy (DR) is one of the most common complications of diabetes and the main cause of blindness.
The progression of the disease can be prevented by early diagnosis of DR.
Due to differences in the distribution of medical conditions and low labor efficiency, the best time for diagnosis and treatment was missed, which results in impaired vision.
Using neural network models to classify and diagnose DR can improve efficiency and reduce costs.
In this work, an improved loss function and three hybrid model structures Hybrid-a, Hybrid-f, and Hybrid-c were proposed to improve the performance of DR classification models.
EfficientNetB4, EfficientNetB5, NASNetLarge, Xception, and InceptionResNetV2 CNNs were chosen as the basic models.
These basic models were trained using enhance cross-entropy loss and cross-entropy loss, respectively.
The output of the basic models was used to train the hybrid model structures.
Experiments showed that enhance cross-entropy loss can effectively accelerate the training process of the basic models and improve the performance of the models under various evaluation metrics.
The proposed hybrid model structures can also improve DR classification performance.
Compared with the best-performing results in the basic models, the accuracy of DR classification was improved from 85.44% to 86.34%, the sensitivity was improved from 98.48% to 98.77%, the specificity was improved from 71.82% to 74.76%, the precision was improved from 90.27% to 91.37%, and the F1 score was improved from 93.62% to 93.9% by using hybrid model structures.
American Psychological Association (APA)
Liu, Hao& Yue, Keqiang& Cheng, Siyi& Pan, Chengming& Sun, Jie& Li, Wenjun. 2020. Hybrid Model Structure for Diabetic Retinopathy Classification. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1186520
Modern Language Association (MLA)
Liu, Hao…[et al.]. Hybrid Model Structure for Diabetic Retinopathy Classification. Journal of Healthcare Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1186520
American Medical Association (AMA)
Liu, Hao& Yue, Keqiang& Cheng, Siyi& Pan, Chengming& Sun, Jie& Li, Wenjun. Hybrid Model Structure for Diabetic Retinopathy Classification. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1186520
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186520