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Validating the accuracy of deep learning for the diagnosis of pneumonia on chest x-ray against a robust multimodal reference diagnosis: a post hoc analysis of two prospective studies.

Jeremy HofmeisterNicolas GarinXavier MontetMax SchefflerAlexandra PlatonPierre-Alexandre PolettiJérôme StirnemannMarie-Pierre DebrayYann-Erick ClaessensXavier DuvalVirginie Prendki
Published in: European radiology experimental (2024)
• We evaluated an openly-access convolutional neural network (CNN) model to diagnose pneumonia on CXRs. • CNN was validated against a strong multimodal reference diagnosis. • In our study, the CNN performance (area under the receiver operating characteristics curve 0.74) was lower than that previously reported when validated against radiologists' diagnosis (0.99 in a recent meta-analysis). • The CNN performance was significantly higher than emergency physicians' (p ≤ 0.022) and comparable to that of board-certified radiologists (p ≥ 0.269).
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