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Role of Artificial Intelligence in COVID-19 Detection
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 sub...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659534/ https://www.ncbi.nlm.nih.gov/pubmed/34884045 http://dx.doi.org/10.3390/s21238045 |
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author | Gudigar, Anjan Raghavendra, U Nayak, Sneha Ooi, Chui Ping Chan, Wai Yee Gangavarapu, Mokshagna Rohit Dharmik, Chinmay Samanth, Jyothi Kadri, Nahrizul Adib Hasikin, Khairunnisa Barua, Prabal Datta Chakraborty, Subrata Ciaccio, Edward J. Acharya, U. Rajendra |
author_facet | Gudigar, Anjan Raghavendra, U Nayak, Sneha Ooi, Chui Ping Chan, Wai Yee Gangavarapu, Mokshagna Rohit Dharmik, Chinmay Samanth, Jyothi Kadri, Nahrizul Adib Hasikin, Khairunnisa Barua, Prabal Datta Chakraborty, Subrata Ciaccio, Edward J. Acharya, U. Rajendra |
author_sort | Gudigar, Anjan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8659534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86595342021-12-10 Role of Artificial Intelligence in COVID-19 Detection Gudigar, Anjan Raghavendra, U Nayak, Sneha Ooi, Chui Ping Chan, Wai Yee Gangavarapu, Mokshagna Rohit Dharmik, Chinmay Samanth, Jyothi Kadri, Nahrizul Adib Hasikin, Khairunnisa Barua, Prabal Datta Chakraborty, Subrata Ciaccio, Edward J. Acharya, U. Rajendra Sensors (Basel) Review 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. MDPI 2021-12-01 /pmc/articles/PMC8659534/ /pubmed/34884045 http://dx.doi.org/10.3390/s21238045 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Gudigar, Anjan Raghavendra, U Nayak, Sneha Ooi, Chui Ping Chan, Wai Yee Gangavarapu, Mokshagna Rohit Dharmik, Chinmay Samanth, Jyothi Kadri, Nahrizul Adib Hasikin, Khairunnisa Barua, Prabal Datta Chakraborty, Subrata Ciaccio, Edward J. Acharya, U. Rajendra Role of Artificial Intelligence in COVID-19 Detection |
title | Role of Artificial Intelligence in COVID-19 Detection |
title_full | Role of Artificial Intelligence in COVID-19 Detection |
title_fullStr | Role of Artificial Intelligence in COVID-19 Detection |
title_full_unstemmed | Role of Artificial Intelligence in COVID-19 Detection |
title_short | Role of Artificial Intelligence in COVID-19 Detection |
title_sort | role of artificial intelligence in covid-19 detection |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659534/ https://www.ncbi.nlm.nih.gov/pubmed/34884045 http://dx.doi.org/10.3390/s21238045 |
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