@article{Mijwil_Aggarwal_Doshi_Hiran_Sundaravadivazhagan_2022, title={Deep Learning Techniques for COVID-19 Detection Based on Chest X-ray and CT-scan Images: A Short Review and Future Perspective}, volume={10}, url={https://ajouronline.com/index.php/AJAS/article/view/6998}, DOI={10.24203/ajas.v10i3.6998}, abstractNote={<p>Today, humans live in the era of rapid growth in electronic devices that are based on artificial intelligence, including the significant growth in the manufacture of machines that perform intelligent human tasks to solve complex situations. Artificial intelligence will significantly influence the development of many domains, especially the medical domain, which relies heavily on artificial intelligence techniques in diagnosing disease data and manufacturing drugs and vaccines. Artificial intelligence has unexpectedly advanced in helping physicians and healthcare workers save many lives, especially during the spread of the COVID-19 virus. This article reviews some literature that have applied deep learning techniques to detect COVID-19 based on chest x-rays and CT-scans images. This article concluded that deep learning techniques have a fundamental and significant role in diagnosing a big dataset of images and assisting specialists in determining whether a person is infected (positive cases).</p> <p> </p>}, number={3}, journal={Asian Journal of Applied Sciences}, author={Mijwil, Maad M. and Aggarwal, Karan and Doshi, Ruchi and Hiran, Kamal Kant and Sundaravadivazhagan, B.}, year={2022}, month={Jul.} }