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CC BY-NC-ND 4.0 · Indian J Radiol Imaging 2021; 31(S 01): S4-S10
DOI: 10.4103/ijri.IJRI_618_20
Review Article

Artificial intelligence and radiology: Combating the COVID-19 conundrum

Mayur Pankhania
Sahyog Imaging Centre, Department of Radiodiagnosis, PDU Medical College and Government Hospital, Rajkot, Gujarat, India
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Abstract

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.

Keywords

Artificial intelligence - COVID-19 - coronavirus - HRCT - radiology


Publication History

Received: 18 July 2020

Accepted: 21 September 2020

Article published online:
13 July 2021

© 2021. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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