Deep Learning Techniques for Automation and Industrial Applications

14Exploring the Potential of Machine Learning and Deep Learning for COVID-19 Detection

Saimul Bashir^1*, Faisal Firdous² and Syed Zoofa Rufai¹

¹Computer Science and Engineering, Chandigarh University, Punjab, India

²Computer Science and Engineering, iNurture Education Solutions Pvt Ltd, Bangalore, India

Abstract

This book chapter presents an extensive review of the application of machine learning and deep learning methods in detecting COVID-19. It emphasizes the significance of early and accurate diagnosis in effectively managing the disease during the COVID-19 pandemic. The chapter encompasses various aspects of machine learning and deep learning techniques, including supervised and unsupervised learning, convolutional neural networks, recurrent neural networks, reinforcement learning, and a comparative analysis of machine learning and deep learning methods for COVID-19 detection.

Moreover, the chapter discusses the challenges and limitations associated with employing machine learning and deep learning techniques for COVID-19 detection. It also explores future research directions in this domain. The primary objective of this chapter is to offer a comprehensive understanding of the potential applications, limitations, and challenges of machine learning and deep learning techniques in COVID-19 disease detection. It aims to serve as a valuable resource for researchers and practitioners involved in the field of COVID-19 diagnosis and machine learning.

Keywords: COVID-19, deep ...