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Deep Transfer Learning Models for Medical Diabetic Retinopathy Detection
- Source :
- Acta Informatica Medica
- Publication Year :
- 2019
- Publisher :
- Academy of Medical sciences, 2019.
-
Abstract
- Introduction Diabetic retinopathy (DR) is the most common diabetic eye disease worldwide and a leading cause of blindness. The number of diabetic patients will increase to 552 million by 2034, as per the International Diabetes Federation (IDF). Aim With advances in computer science techniques, such as artificial intelligence (AI) and deep learning (DL), opportunities for the detection of DR at the early stages have increased. This increase means that the chances of recovery will increase and the possibility of vision loss in patients will be reduced in the future. Methods In this paper, deep transfer learning models for medical DR detection were investigated. The DL models were trained and tested over the Asia Pacific Tele-Ophthalmology Society (APTOS) 2019 dataset. According to literature surveys, this research is considered one the first studies to use of the APTOS 2019 dataset, as it was freshly published in the second quarter of 2019. The selected deep transfer models in this research were AlexNet, Res-Net18, SqueezeNet, GoogleNet, VGG16, and VGG19. These models were selected, as they consist of a small number of layers when compared to larger models, such as DenseNet and InceptionResNet. Data augmentation techniques were used to render the models more robust and to overcome the overfitting problem. Results The testing accuracy and performance metrics, such as the precision, recall, and F1 score, were calculated to prove the robustness of the selected models. The AlexNet model achieved the highest testing accuracy at 97.9%. In addition, the achieved performance metrics strengthened our achieved results. Moreover, AlexNet has a minimum number of layers, which decreases the training time and the computational complexity.
- Subjects :
- Computer science
0211 other engineering and technologies
Convolutional Neural Network
02 engineering and technology
Overfitting
Machine learning
computer.software_genre
Convolutional neural network
Diabetic Eye Disease
Machine Learning
Robustness (computer science)
0202 electrical engineering, electronic engineering, information engineering
medicine
021110 strategic, defence & security studies
Original Paper
Diabetic Retinopathy
business.industry
Deep learning
General Medicine
Diabetic retinopathy
medicine.disease
Deep Transfer Learning
020201 artificial intelligence & image processing
Artificial intelligence
Transfer of learning
business
F1 score
computer
Subjects
Details
- Language :
- English
- ISSN :
- 19865988 and 03538109
- Volume :
- 27
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Acta Informatica Medica
- Accession number :
- edsair.doi.dedup.....490fd19483fcda3cf818a4d521d85b19