Imperial College London
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Mr. Gareth G. Jones

Faculty of Medicine, Department of Surgery & Cancer

Clinical Senior Lecturer in Orthopaedic Surgery
 
 
 
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Contact

 

+44 (0)20 7594 5465g.g.jones

 
 
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Location

 

203Sir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{York:2023:10.1186/s12909-022-03976-6,
author = {York, T and Raj, S and Ashdown, T and Jones, G},
doi = {10.1186/s12909-022-03976-6},
journal = {BMC Medical Education},
pages = {1--10},
title = {Clinician and computer: a study on doctors’ perceptions of artificial intelligence in skeletal radiography},
url = {http://dx.doi.org/10.1186/s12909-022-03976-6},
volume = {23},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundTraumatic musculoskeletal injuries are a common presentation to emergency care, the first-line investigation often being plain radiography. The interpretation of this imaging frequently falls to less experienced clinicians despite well-established challenges in reporting. This study presents novel data of clinicians’ confidence in interpreting trauma radiographs, their perception of AI in healthcare, and their support for the development of systems applied to skeletal radiography.MethodsA novel questionnaire was distributed through a network of collaborators to clinicians across the Southeast of England. Over a three-month period, responses were compiled into a database before undergoing statistical review.ResultsThe responses of 297 participants were included. The mean self-assessed knowledge of AI in healthcare was 3.68 out of ten, with significantly higher knowledge reported by the most senior doctors (Specialty Trainee/Specialty Registrar or above = 4.88). 13.8% of participants reported an awareness of AI in their clinical practice.Overall, participants indicated substantial favourability towards AI in healthcare (7.87) and in AI applied to skeletal radiography (7.75). There was a preference for a hypothetical system indicating positive findings rather than ruling as negative (7.26 vs 6.20).ConclusionsThis study identifies clear support, amongst a cross section of student and qualified doctors, for both the general use of AI technology in healthcare and in its application to skeletal radiography for trauma. The development of systems to address this demand appear well founded and popular. The engagement of a small but reticent minority should be sought, along with improving the wider education of doctors on AI.
AU  - York,T
AU  - Raj,S
AU  - Ashdown,T
AU  - Jones,G
DO  - 10.1186/s12909-022-03976-6
EP  - 10
PY  - 2023///
SN  - 1472-6920
SP  - 1
TI  - Clinician and computer: a study on doctors’ perceptions of artificial intelligence in skeletal radiography
T2  - BMC Medical Education
UR  - http://dx.doi.org/10.1186/s12909-022-03976-6
UR  - https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-022-03976-6
UR  - http://hdl.handle.net/10044/1/102265
VL  - 23
ER  -
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