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Clin Radiol2021;76(6):473.e9-473.e15.June 1, 2021Journal Article

Diagnosis of normal chest radiographs using an autonomous deep-learning algorithm.

T Dyer1, L Dillard2, M Harrison2, T Naunton Morgan2, R Tappouni3, Q Malik4, S Rasalingham2
1Behold.ai Technologies Limited, WeWork South Bank, 22 Upper Ground, London, SE1 9PD, UK. Electronic address: tomd@behold.ai.
2Behold.ai Technologies Limited, WeWork South Bank, 22 Upper Ground, London, SE1 9PD, UK.
3Behold.ai Technologies Limited, WeWork South Bank, 22 Upper Ground, London, SE1 9PD, UK; Department of Radiology, Wake Forest Baptist Health, North Carolina, USA.
4Behold.ai Technologies Limited, WeWork South Bank, 22 Upper Ground, London, SE1 9PD, UK; Department of Radiology, Basildon and Thurrock NHS Trust, Essex, UK.
PubMed DOI

Abstract

AIM: To evaluate the suitability of a deep-learning (DL) algorithm for identifying normality as a rule-out test for fully automated diagnosis in frontal adult chest radiographs (CXR) in an active clinical pathway. MATERIALS AND METHODS: This multicentre study included 3,887 CXRs from four distinct NHS institutions. A convolutional neural network (CNN) was developed and trained prior to this study…

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