Covid-19 Detection Using AI

Authors

  • Shashank Mishra  Department of Computer Science and Engineering Babu Banarasi Das Institute of Technology and Management, Lucknow, Uttar Pradesh , India
  • Himanshu Kumar Shukla  Department of Computer Science and Engineering Babu Banarasi Das Institute of Technology and Management, Lucknow, Uttar Pradesh , India
  • Rajiv Singh  Department of Computer Science and Engineering Babu Banarasi Das Institute of Technology and Management, Lucknow, Uttar Pradesh , India
  • Vivek Pandey  Department of Computer Science and Engineering Babu Banarasi Das Institute of Technology and Management, Lucknow, Uttar Pradesh , India
  • Shubham Sagar  Department of Computer Science and Engineering Babu Banarasi Das Institute of Technology and Management, Lucknow, Uttar Pradesh , India
  • Yasasvi Singh  Department of Computer Science and Engineering Babu Banarasi Das Institute of Technology and Management, Lucknow, Uttar Pradesh , India

DOI:

https://doi.org/10.32628/IJSRSET2183130

Keywords:

Deep learning, CNN Algorithm Chest X-Ray Neural Network

Abstract

The sudden increase in COVID-19 patients is a major shock to our global health care systems. With limited availability of test kits, it is not possible for all patients with respiratory infections to be tested using RT-PCR. Testing also takes a long time, with limited sensitivity. The detection of COVID-19 infections on Chest X-Ray can help isolate patients at high risk while awaiting test results. X-Ray machines are already available in many health care systems, and with many modern X-Ray systems already installed on the computer, there is no travel time involved in the samples. In this work we propose the use of chest X-Ray to prioritize the selection of patients for further RT-PCR testing. This can be useful in a hospital setting where current systems have difficulty deciding whether to keep the patient in the ward with other patients or isolate them from COVID-19 areas. It may also be helpful in identifying patients with high risk of COVID with false positive RT-PCR that will require repeated testing. In addition, we recommend the use of modern AI techniques to detect COVID-19 patients who use X-Ray imaging in an automated manner, especially in areas where radiologists are not available, and help make the proposed diagnostic technology easier. Introducing the CovidAID: COVID-19 AI Detector, a model based on a deep neural network of screening patients for proper diagnosis. In a publicly available covid-chest x-ray-dataset [2], our model provides 90.5% accuracy with 100% sensitivity (remember) to COVID-19 infection. We are greatly improving the results of Covid-Net [10] on the same database.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2021-06-30

Issue

Volume 8, Issue 3, May-June-2021

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Shashank Mishra, Himanshu Kumar Shukla, Rajiv Singh, Vivek Pandey, Shubham Sagar, Yasasvi Singh "Covid-19 Detection Using AI" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 3, pp.561-566, May-June-2021. Available at doi : https://doi.org/10.32628/IJSRSET2183130