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Artificial Intelligence (AI) in the diagonosis of COVIS-19 Detection: A Review
28th IEEE International Conference on Electronics, Circuits, and Systems (IEEE ICECS) ; 2021.
Article in English | Web of Science | ID: covidwho-1819833
ABSTRACT
Coronaviruses are a large viral family that attacks key organs, particularly the lungs. The infection spread is growing by the day, affecting almost every industry. Various Artificial Intelligence studies have been proposed, to learn the measurable information of people who have been affected with COVID-19 and those who have recovered, as well as the death rate. Various data samples like chest images, lung images, swab results, blood samples, and CT scans are used to predict the COVID-19. The paper gives an in-depth look at how AI and machine learning techniques can be used to accurately predict COVID-19. The proposed review is centered around investigating the different AI methods, models, and logical registering procedures used in foreseeing the COVID-19 sickness. The study also summarizes the difficulties associated with current methods and future exploration works.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: 28th IEEE International Conference on Electronics, Circuits, and Systems (IEEE ICECS) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: 28th IEEE International Conference on Electronics, Circuits, and Systems (IEEE ICECS) Year: 2021 Document Type: Article