Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment

被引:31
作者
Hasan, Md. Mahadi [1 ]
Islam, Muhammad Usama [2 ]
Sadeq, Muhammad Jafar [1 ]
Fung, Wai-Keung [3 ]
Uddin, Jasim [3 ]
机构
[1] Asian Univ Bangladesh, Dept Comp Sci & Engn, Ashulia 1349, Bangladesh
[2] Univ Louisiana Lafayette, Sch Comp & Informat, Lafayette, LA 70504 USA
[3] Cardiff Metropolitan Univ, Cardiff Sch Technol, Dept Appl Comp & Engn, Cardiff CF5 2YB, Wales
关键词
COVID-19; artificial intelligence; machine learning; deep learning; few-shot learning; COMPUTER-AIDED DIAGNOSIS; CT IMAGE SEGMENTATION; DEEP; NETWORK; CLASSIFICATION; MORTALITY; INFECTION; FRAMEWORK; CLASSIFY; FUSION;
D O I
10.3390/s23010527
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly the healthcare sector. With the rise of the COVID-19 pandemic, several prediction and detection methods using artificial intelligence have been employed to understand, forecast, handle, and curtail the ensuing threats. In this study, the most recent related publications, methodologies and medical reports were investigated with the purpose of studying artificial intelligence's role in the pandemic. This study presents a comprehensive review of artificial intelligence with specific attention to machine learning, deep learning, image processing, object detection, image segmentation, and few-shot learning studies that were utilized in several tasks related to COVID-19. In particular, genetic analysis, medical image analysis, clinical data analysis, sound analysis, biomedical data classification, socio-demographic data analysis, anomaly detection, health monitoring, personal protective equipment (PPE) observation, social control, and COVID-19 patients' mortality risk approaches were used in this study to forecast the threatening factors of COVID-19. This study demonstrates that artificial-intelligence-based algorithms integrated into Internet of Things wearable devices were quite effective and efficient in COVID-19 detection and forecasting insights which were actionable through wide usage. The results produced by the study prove that artificial intelligence is a promising arena of research that can be applied for disease prognosis, disease forecasting, drug discovery, and to the development of the healthcare sector on a global scale. We prove that artificial intelligence indeed played a significantly important role in helping to fight against COVID-19, and the insightful knowledge provided here could be extremely beneficial for practitioners and research experts in the healthcare domain to implement the artificial-intelligence-based systems in curbing the next pandemic or healthcare disaster.
引用
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页数:35
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