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An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice

Assessing the current Artificial intelligence (AI) situation is a crucial step towards its implementation into radiology practice. The study aimed to assess radiographer willingness to accept AI in radiology work practice and the impact of AI in work performance. An exploratory cross-sectional onlin...

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Autores principales: Abuzaid, Mohamed M., Elshami, Wiam, McConnell, Jonathan, Tekin, H. O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342654/
https://www.ncbi.nlm.nih.gov/pubmed/34377625
http://dx.doi.org/10.1007/s12553-021-00583-1
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author Abuzaid, Mohamed M.
Elshami, Wiam
McConnell, Jonathan
Tekin, H. O.
author_facet Abuzaid, Mohamed M.
Elshami, Wiam
McConnell, Jonathan
Tekin, H. O.
author_sort Abuzaid, Mohamed M.
collection PubMed
description Assessing the current Artificial intelligence (AI) situation is a crucial step towards its implementation into radiology practice. The study aimed to assess radiographer willingness to accept AI in radiology work practice and the impact of AI in work performance. An exploratory cross-sectional online survey conducted for radiographers working within the Middle East and India was conducted from May–August 2020. A previously validated survey used to obtain radiographer's demographics, knowledge, perceptions, organization readiness, and challenges of integrating AI into radiology. The survey was accessible for radiographers and distributed through the societies page. The survey was completed by 549 radiographers distributed as (77.6%, n = 426) from the Middle East while (22.4%, n = 123) from India. A majority (86%, n = 773) agreed that AI currently plays an important role in radiology and (88.0%, n = 483) expected that AI would play a role in radiology practice and image production. The challenges for AI implementation in practice were developing AI skills (42.8%, n = 235) and AI knowledge development (37.0%, n = 203). Participants showed high interest to integrate AI in under and postgraduate curriculum. There is excitement about what AI could offer, but education input is a requirement. Fears are expressed about job security and how radiology may work across all ages and educational backgrounds. Radiographers become aware of AI role and challenges, which can be improved by education and training.
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spelling pubmed-83426542021-08-06 An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice Abuzaid, Mohamed M. Elshami, Wiam McConnell, Jonathan Tekin, H. O. Health Technol (Berl) Original Paper Assessing the current Artificial intelligence (AI) situation is a crucial step towards its implementation into radiology practice. The study aimed to assess radiographer willingness to accept AI in radiology work practice and the impact of AI in work performance. An exploratory cross-sectional online survey conducted for radiographers working within the Middle East and India was conducted from May–August 2020. A previously validated survey used to obtain radiographer's demographics, knowledge, perceptions, organization readiness, and challenges of integrating AI into radiology. The survey was accessible for radiographers and distributed through the societies page. The survey was completed by 549 radiographers distributed as (77.6%, n = 426) from the Middle East while (22.4%, n = 123) from India. A majority (86%, n = 773) agreed that AI currently plays an important role in radiology and (88.0%, n = 483) expected that AI would play a role in radiology practice and image production. The challenges for AI implementation in practice were developing AI skills (42.8%, n = 235) and AI knowledge development (37.0%, n = 203). Participants showed high interest to integrate AI in under and postgraduate curriculum. There is excitement about what AI could offer, but education input is a requirement. Fears are expressed about job security and how radiology may work across all ages and educational backgrounds. Radiographers become aware of AI role and challenges, which can be improved by education and training. Springer Berlin Heidelberg 2021-08-06 2021 /pmc/articles/PMC8342654/ /pubmed/34377625 http://dx.doi.org/10.1007/s12553-021-00583-1 Text en © IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Abuzaid, Mohamed M.
Elshami, Wiam
McConnell, Jonathan
Tekin, H. O.
An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
title An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
title_full An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
title_fullStr An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
title_full_unstemmed An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
title_short An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
title_sort extensive survey of radiographers from the middle east and india on artificial intelligence integration in radiology practice
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342654/
https://www.ncbi.nlm.nih.gov/pubmed/34377625
http://dx.doi.org/10.1007/s12553-021-00583-1
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