Prospective, comparative evaluation of a deep neural network and dermoscopy in the diagnosis of onychomycosis

PloS One
Young Jae KimSung Eun Chang

Abstract

Onychomycosis is the most common nail disorder and is associated with diagnostic challenges. Emerging non-invasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of this condition. However, comparative studies of the two tools in the diagnosis of onychomycosis have not previously been conducted. This study evaluated the diagnostic abilities of a deep neural network (http://nail.modelderm.com) and dermoscopic examination in patients with onychomycosis. A prospective observational study was performed in patients presenting with dystrophic features in the toenails. Clinical photographs were taken by research assistants, and the ground truth was determined either by direct microscopy using the potassium hydroxide test or by fungal culture. Five board-certified dermatologists determined a diagnosis of onychomycosis using the clinical photographs. The diagnosis was also made using the algorithm and dermoscopic examination. A total of 90 patients (mean age, 55.3; male, 43.3%) assessed between September 2018 and July 2019 were included in the analysis. The detection of onychomycosis using the algorithm (AUC, 0.751; 95% CI, 0.646-0.856) and that by dermoscopy (AUC, 0....Continue Reading

References

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Citations

Oct 20, 2020·Frontiers in Medicine·Kenneth ThomsenOle Winther
Mar 26, 2021·Journal of the European Academy of Dermatology and Venereology : JEADV·A K GuptaE M Quinlan
Dec 18, 2021·Journal of Cosmetic Dermatology·Aditya K Gupta, Deanna C Hall

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BETA
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Caffe
CNN
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