Intelligent system for COVID-19 prognosis: a state-of-the-art survey

Janmenjoy Nayak; Bighnaraj Naik; Paidi Dinesh; Kanithi Vakula; B Kameswara Rao; Weiping Ding; Danilo Pelusi

doi:10.1007/s10489-020-02102-7

Intelligent system for COVID-19 prognosis: a state-of-the-art survey

Appl Intell (Dordr). 2021;51(5):2908-2938. doi: 10.1007/s10489-020-02102-7. Epub 2021 Jan 6.

Authors

Janmenjoy Nayak¹, Bighnaraj Naik², Paidi Dinesh³, Kanithi Vakula³, B Kameswara Rao¹, Weiping Ding⁴, Danilo Pelusi⁵

Affiliations

¹ Department of Computer Science and Engineering, Aditya Institute of Technology and Management (AITAM), K Kotturu, Tekkali, AP 532201 India.
² Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Odisha 768018 India.
³ Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, AP 532402 India.
⁴ School of Information Science and Technology, Nantong University, Nantong, China.
⁵ Faculty of Communication Sciences, University of Teramo, Coste Sant&#39, Agostino Campus, Teramo, Italy.

Abstract

This 21st century is notable for experiencing so many disturbances at economic, social, cultural, and political levels in the entire world. The outbreak of novel corona virus 2019 (COVID-19) has been treated as a Public Health crisis of global Concern by the World Health Organization (WHO). Various outbreak models for COVID-19 are being utilized by researchers throughout the world to get well-versed decisions and impose significant control measures. Amid the standard methods for COVID-19 worldwide epidemic prediction, easy statistical, as well as epidemiological methods have got more consideration by researchers and authorities. One main difficulty in controlling the spreading of COVID-19 is the inadequacy and lack of medical tests for detecting as well as identifying a solution. To solve this problem, a few statistical-based advances are being enhanced and turn into a partial resolution up-to some level. To deal with the challenges of the medical field, a broad range of intelligent based methods, frameworks, and equipment have been recommended by Machine Learning (ML) and Deep Learning. As ML and DL have the ability of identifying and predicting patterns in complex large datasets, they are recognized as a suitable procedure for producing effective solutions for the diagnosis of COVID-19. In this paper, a perspective research has been conducted in the applicability of intelligent systems such as ML, DL and others in solving COVID-19 related outbreak issues. The main intention behind this study is (i) to understand the importance of intelligent approaches such as ML and DL for COVID-19 pandemic, (ii) discussing the efficiency and impact of these methods in the prognosis of COVID-19, (iii) the growth in the development of type of ML and advanced ML methods for COVID-19 prognosis,(iv) analyzing the impact of data types and the nature of data along with challenges in processing the data for COVID-19,(v) to focus on some future challenges in COVID-19 prognosis to inspire the researchers for innovating and enhancing their knowledge and research on other impacted sectors due to COVID-19.

Keywords: COVID-19; Deep learning; Intelligent system; Machine learning; Mathematical model.