AI in Diagnostic Radiology: What Happens When Algorithms Are Updated

Martine R. Skregelid; Kasim Ibrahim-pur; Flemming Skjøth; Malene Roland Pedersen; Helle Precht

doi:10.3390/radiation6010004

AI in Diagnostic Radiology: What Happens When Algorithms Are Updated

Martine R. Skregelid
, Kasim Ibrahim-pur
, Flemming Skjøth
, Malene Roland Pedersen
, Helle Precht

Radiografuddannelsen Herning

Publikation: Bidrag til tidsskrift › Tidsskriftsartikel › Forskning › peer review

Abstract

Hand and ankle fractures are common and can easily be missed in busy emergency departments. Therefore, many hospitals now use artificial intelligence (AI) to highlight possible fractures. AI software is frequently updated, and regular evaluation is warranted to assesswhether new updates alter the diagnostic performance. In this study, we investigated the diagnostic accuracy of two different versions of the same AI fracture detection software on hand and ankle radiographs, using reporting radiographers’ reports as the reference standard. We also assessed whether AI output led to changes in reporting radiographers’ assessments in cases of disagreement.

Originalsprog	Engelsk
Artikelnummer	4
Tidsskrift	Radiation
Vol/bind	6
Udgave nummer	1
Antal sider	12
ISSN	2673-592X
DOI	https://doi.org/10.3390/radiation6010004
Status	Udgivet - jan. 2026

Emneord

Kliniske undersøgelsesmetoder, laboratorieteknologi og radiografi

Adgang til dokumentet

10.3390/radiation6010004Licens: CC BY-ND

Citationsformater

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AU - Skregelid, Martine R.

AU - Ibrahim-pur, Kasim

AU - Skjøth, Flemming

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AU - Precht, Helle

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N2 - Hand and ankle fractures are common and can easily be missed in busy emergency departments. Therefore, many hospitals now use artificial intelligence (AI) to highlight possible fractures. AI software is frequently updated, and regular evaluation is warranted to assesswhether new updates alter the diagnostic performance. In this study, we investigated the diagnostic accuracy of two different versions of the same AI fracture detection software on hand and ankle radiographs, using reporting radiographers’ reports as the reference standard. We also assessed whether AI output led to changes in reporting radiographers’ assessments in cases of disagreement.

AB - Hand and ankle fractures are common and can easily be missed in busy emergency departments. Therefore, many hospitals now use artificial intelligence (AI) to highlight possible fractures. AI software is frequently updated, and regular evaluation is warranted to assesswhether new updates alter the diagnostic performance. In this study, we investigated the diagnostic accuracy of two different versions of the same AI fracture detection software on hand and ankle radiographs, using reporting radiographers’ reports as the reference standard. We also assessed whether AI output led to changes in reporting radiographers’ assessments in cases of disagreement.

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