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

Public Health
Medicine

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