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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM30777
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The abstract of the document discusses the use of convolutional neural networks (CNN) and support vector machines (SVM) to detect Covid-19 patients based on X-ray chest images. The study focuses on using the ResNet-50 model to extract features from the images and classify them using SVM. The results show high sensitivity and overall performance values for Covid-19 detection. The study suggests that this method can be beneficial for radiology specialists and help reduce false detection rates. These methods offer potential solutions for the early and accurate diagnosis of COVID-19 patients using X-ray imaging.
KEYWORDS
Publication Date
12/31/45396
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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