Correction: Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT (European Radiology Experimental, (2024), 8, 1, (63), 10.1186/s41747-024-00459-9)

Research output: Contribution to journalErratum

5 Downloads (Pure)

Abstract

https://doi.org/10.1186/s41747-024-00459-9, published online 20 May 2024 In the original article, the results section “Performance evaluation and comparison” displays two statements that the authors wish to clarify to remove ambiguity: On page 6, “Sensitivity of AI was not significantly different for either the emphysema (p = 0.320) or the non-emphysema group (p = 0.090).”, should instead read: “Sensitivity was not significantly different between the emphysema and non-emphysema group for either AI (p = 0.80) or human reader (p = 0.54).” On page 7, “Also, the nodule detection sensitivity in emphysema tended to be higher for AI than the human reader, but there were no significant differences for either the emphysema (p = 0.310) or the non-emphysema group (p = 1.000).” should instead read: “Also, the nodule detection sensitivity in emphysema tended to be higher for AI than the human reader, but no significant differences were found between the emphysema and the non-emphysema group for either AI (0.94) or human reader (p = 0.29).” On page 6, “Sensitivity of AI was not significantly different for either the emphysema (p = 0.320) or the non-emphysema group (p = 0.090).”, should instead read: “Sensitivity was not significantly different between the emphysema and non-emphysema group for either AI (p = 0.80) or human reader (p = 0.54).” On page 7, “Also, the nodule detection sensitivity in emphysema tended to be higher for AI than the human reader, but there were no significant differences for either the emphysema (p = 0.310) or the non-emphysema group (p = 1.000).” should instead read: “Also, the nodule detection sensitivity in emphysema tended to be higher for AI than the human reader, but no significant differences were found between the emphysema and the non-emphysema group for either AI (0.94) or human reader (p = 0.29).”.

Original languageEnglish
Article number94
Number of pages1
JournalEuropean Radiology Experimental
Volume8
Issue number1
DOIs
Publication statusPublished - 16-Aug-2024

Fingerprint

Dive into the research topics of 'Correction: Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT (European Radiology Experimental, (2024), 8, 1, (63), 10.1186/s41747-024-00459-9)'. Together they form a unique fingerprint.

Cite this