Automated Diagnostic Radiographs of COVID-19 Based on Deep Learning Method
2022 IET International Conference on Engineering Technologies and Applications, IET-ICETA 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2191944
ABSTRACT
The COVID-19 outbreak has had a serious impact on Taiwan's health care system. Deep Learning is an effective technology to help doctors make the most appropriate medical decisions for every patient in this crisis. In this study, we select four state-of-the-art Deep Learning-Xception, MobileNetv2, DenseNet169, and DenseNet201. Additionally, Transfer Learning is used for pre-training them before four models individually classify normal and positive COVID-19 chest X-ray images. Lastly, the best results reached 98.58% accuracy, 98.58% precision, and 98.42% recall. © 2022 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2022 IET International Conference on Engineering Technologies and Applications, IET-ICETA 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS