Published August 30, 2023 | Version CC BY-NC-ND 4.0
Journal article Open

A Comparative Evaluation of Diverse Deep Learning Models for the COVID-19 Prediction

Creators

  • 1. Research Scholar, Department of Instrumentation and Control, Gujarat Technological University, Ahmedabad (Gujarat), India.
  • 2. Associate Prof. & Head, Department of Instrumentation & Control Engineering, Vishwakarma Government Engineering College, Chandkheda, (Gujarat), India.
  • 3. Assistant Prof., Department of Instrumentation & Control Engineering, Government Engineering College, Rajkot (Gujarat), India.
  • 4. Data Scientist, KRiAN GmbH, Wolfsburg, Germany.
  • 5. Senior Machine Learning Engineer, Autodesk, Toronto, Ontario, Canada.

Contributors

Contact person:

  • 1. Research Scholar, Department of Instrumentation and Control, Gujarat Technological University, Ahmedabad (Gujarat), India.

Description

Abstract: Deep learning methodologies are now feasible in practically every sphere of modern life because to technological advancements. Because of its high level of accuracy, deep learning can automatically diagnose and classify a wide variety of medical conditions in the field of medicine. The coronavirus first appeared in Wuhan, China, in December 2019, and quickly spread throughout the world. The pandemic of COVID-19 presented significant challenges to the world's health care system. PCR and medical imaging can diagnose COVID-19. There has a negative impact on the health of people as well as the global economy, education, and social life. The most significant challenge in stymieing the rapid propagation of the disease is locating positive Corona patients as promptly as possible. Because there are no automated tool kits, additional diagnostic equipment will be required. According to radiological studies, these images include important information about the coronavirus. Accurate treatment of this virus and a solution to the problem of a lack of medical professionals in remote areas may be possible with the help of a specialized Artificial Intelligence (AI) system and radiographic pictures. We used pre-trained CNN models Xception, Inception, ResNet-50, ResNet-50V2, DenseNet121, and MobileNetV2 to correct the COVID-19 classification analytics. In this paper, we investigate COVID-19 detection methods that make use of chest X-rays. According to the findings of our research, the pre-trained CNN Model that makes use of MobileNetV2 performs better than other CNN techniques in terms of both the size of the solution and its speed. Our method might be of use to researchers in the process of fine-tuning the CNN model for efficient COVID screening.

Notes

Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved.

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ISSN: 2278-3075 (Online)
https://portal.issn.org/resource/ISSN/2278-3075#
Retrieval Number: 100.1/ijitee.I96960812923
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Publisher: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
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