1.
Clinical Infection in Practice
; 17, 2023.
Article
in English
| EMBASE | ID: covidwho-2243711
2.
1st International Conference on Ambient Intelligence in Health Care, ICAIHC 2021
; 317:225-230, 2023.
Article
in English
| Scopus | ID: covidwho-2173920
ABSTRACT
Analysis of chest X-ray images of COVID infected patients is one of the important diagnostic strategies. The manual identification of these images may be erroneous and faulty. So the computer-aided diagnosis of COVID infections using deep learning techniques is becoming useful. In this paper, the classification of chest X-ray images using CNN is conducted, and the performance of different optimizers is studied. The dataset containing chest X-ray images of normal and COVID infected patients is collected from Kaggle. The experimental study suggested that Adam optimizer achieved 95.83% classification accuracy, and it outperformed the other three optimizers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.