Gudigar, Anjan and Raghavendra, Udupi and Nayak, Sneha and Ooi, Chui Ping and Chan, Wai Yee and Gangavarapu, Mokshagna Rohit and Dharmik, Chinmay and Samanth, Jyothi and Kadri, Nahrizul Adib and Hasikin, Khairunnisa and Barua, Prabal Datta and Chakraborty, Subrata and Ciaccio, Edward J. and Acharya, U. Rajendra (2021) Role of artificial intelligence in COVID-19 detection. Sensors, 21 (23). ISSN 1424-8220, DOI https://doi.org/10.3390/s21238045.
Full text not available from this repository.Abstract
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.
| Item Type: | Article |
|---|---|
| Funders: | Ministry of Education, Malaysia[MRUN2019-3D] |
| Uncontrolled Keywords: | Artificial intelligence;Computer-aided diagnostic tool;Deep neural networks;Hand-crafted feature learning;Supervised learning |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine R Medicine > R Medicine (General) > Medical technology |
| Divisions: | Faculty of Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 14 Sep 2022 04:37 |
| Last Modified: | 14 Sep 2022 04:37 |
| URI: | http://eprints.um.edu.my/id/eprint/34509 |
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