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Can a computer sense the symptoms of osteoarthritis from a radiograph? Initial findings from a pilot, AI approach to osteoarthritis assessment

Can a computer sense the symptoms of osteoarthritis from a radiograph? Initial findings from a pilot, AI approach to osteoarthritis assessment
Can a computer sense the symptoms of osteoarthritis from a radiograph? Initial findings from a pilot, AI approach to osteoarthritis assessment
Osteoarthritis is the most common joint disease and is associated with substantial morbidity for the affected individual and a significant financial burden for the health system at large. There is a marked discrepancy between the extent of osteoarthritis observed via plain radiography and the magnitude of clinical symptoms. For this reason we aimed to investigate whether, using an artificial intelligence approach, we could train an algorithm to diagnose osteoarthritis and if we were able to find correlations between clinical symptoms and radiographic images.
British Society for Rheumatology
Pereira, Diogo
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Fuggle, Nick
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Mahmoodi, Sasan
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Cooper, Cyrus
e05f5612-b493-4273-9b71-9e0ce32bdad6
Pereira, Diogo
4c713ed2-b00d-40b0-819b-7bfff1cc54c9
Fuggle, Nick
9ab0c81a-ac67-41c4-8860-23e0fdb1a900
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Cooper, Cyrus
e05f5612-b493-4273-9b71-9e0ce32bdad6

Pereira, Diogo, Fuggle, Nick, Mahmoodi, Sasan and Cooper, Cyrus (2021) Can a computer sense the symptoms of osteoarthritis from a radiograph? Initial findings from a pilot, AI approach to osteoarthritis assessment. In Abstract in Rheumatology. vol. 16, British Society for Rheumatology. 2 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Osteoarthritis is the most common joint disease and is associated with substantial morbidity for the affected individual and a significant financial burden for the health system at large. There is a marked discrepancy between the extent of osteoarthritis observed via plain radiography and the magnitude of clinical symptoms. For this reason we aimed to investigate whether, using an artificial intelligence approach, we could train an algorithm to diagnose osteoarthritis and if we were able to find correlations between clinical symptoms and radiographic images.

Text
BSR21 OA Computer Vision abstract 20_10_07
Restricted to Repository staff only until 10 May 2021.
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More information

Accepted/In Press date: 8 February 2021
Venue - Dates: British Society of Rheumatology Annual Conference, , Virtual, 2021-04-26 - 2021-04-28

Identifiers

Local EPrints ID: 446462
URI: http://eprints.soton.ac.uk/id/eprint/446462
PURE UUID: 4a7ea599-c496-4ca7-98ef-f4276ba7c1e6
ORCID for Cyrus Cooper: ORCID iD orcid.org/0000-0003-3510-0709

Catalogue record

Date deposited: 10 Feb 2021 17:33
Last modified: 18 Feb 2021 16:48

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