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Artificial intelligence and radiology: Combating the COVID-19 conundrum

The COVID-19 pandemic has necessitated rapid testing and diagnosis to manage its spread. While reverse transcriptase polymerase chain reaction (RT-PCR) is being used as the gold standard method to diagnose COVID-19, many scientists and doctors have pointed out some challenges related to the variabil...

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Autor principal: Pankhania, Mayur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996687/
https://www.ncbi.nlm.nih.gov/pubmed/33814755
http://dx.doi.org/10.4103/ijri.IJRI_618_20
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author Pankhania, Mayur
author_facet Pankhania, Mayur
author_sort Pankhania, Mayur
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description The COVID-19 pandemic has necessitated rapid testing and diagnosis to manage its spread. While reverse transcriptase polymerase chain reaction (RT-PCR) is being used as the gold standard method to diagnose COVID-19, many scientists and doctors have pointed out some challenges related to the variability, accuracy, and affordability of this technique. At the same time, radiological methods, which were being used to diagnose COVID-19 in the early phase of the pandemic in China, were sidelined by many primarily due to their low specificity and the difficulty in conducting a differential diagnosis. However, the utility of radiological methods cannot be neglected. Indeed, over the past few months, healthcare consultants and radiologists in India have been using or advising the use of high-resolution computed tomography (HRCT) of the chest for early diagnosis and tracking of COVID-19, particularly in preoperative and asymptomatic patients. At the same time, scientists have been trying to improve upon the radiological method of COVID-19 diagnosis and monitoring by using artificial intelligence (AI)-based interpretation models. This review is an effort to compile and compare such efforts. To this end, the latest scientific literature on the use of radiology and AI-assisted radiology for the diagnosis and monitoring of COVID-19 has been reviewed and presented, highlighting the strengths and limitations of such techniques.
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spelling pubmed-79966872021-04-01 Artificial intelligence and radiology: Combating the COVID-19 conundrum Pankhania, Mayur Indian J Radiol Imaging Review Article The COVID-19 pandemic has necessitated rapid testing and diagnosis to manage its spread. While reverse transcriptase polymerase chain reaction (RT-PCR) is being used as the gold standard method to diagnose COVID-19, many scientists and doctors have pointed out some challenges related to the variability, accuracy, and affordability of this technique. At the same time, radiological methods, which were being used to diagnose COVID-19 in the early phase of the pandemic in China, were sidelined by many primarily due to their low specificity and the difficulty in conducting a differential diagnosis. However, the utility of radiological methods cannot be neglected. Indeed, over the past few months, healthcare consultants and radiologists in India have been using or advising the use of high-resolution computed tomography (HRCT) of the chest for early diagnosis and tracking of COVID-19, particularly in preoperative and asymptomatic patients. At the same time, scientists have been trying to improve upon the radiological method of COVID-19 diagnosis and monitoring by using artificial intelligence (AI)-based interpretation models. This review is an effort to compile and compare such efforts. To this end, the latest scientific literature on the use of radiology and AI-assisted radiology for the diagnosis and monitoring of COVID-19 has been reviewed and presented, highlighting the strengths and limitations of such techniques. Wolters Kluwer - Medknow 2021-01 2021-01-23 /pmc/articles/PMC7996687/ /pubmed/33814755 http://dx.doi.org/10.4103/ijri.IJRI_618_20 Text en Copyright: © 2021 Indian Journal of Radiology and Imaging http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Review Article
Pankhania, Mayur
Artificial intelligence and radiology: Combating the COVID-19 conundrum
title Artificial intelligence and radiology: Combating the COVID-19 conundrum
title_full Artificial intelligence and radiology: Combating the COVID-19 conundrum
title_fullStr Artificial intelligence and radiology: Combating the COVID-19 conundrum
title_full_unstemmed Artificial intelligence and radiology: Combating the COVID-19 conundrum
title_short Artificial intelligence and radiology: Combating the COVID-19 conundrum
title_sort artificial intelligence and radiology: combating the covid-19 conundrum
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996687/
https://www.ncbi.nlm.nih.gov/pubmed/33814755
http://dx.doi.org/10.4103/ijri.IJRI_618_20
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