External clinical validation of automated software to identify structural abnormalities and microhaemorrhages in nailfold videocapillaroscopy images.

Borja C Gracia Tello, Eduardo Ramos Ibañez,Luis Saez Comet,Alfredo Guillén Del Castillo,Carmen Pilar Simeón Aznar, Albert Selva O'Callaghan,Gerard Espinosa,Gema Lledó,Mayka Freire Dapena,Elena Martinez Robles,Juan José Ríos,José Antonio Todolí Parra, Begoña Marí Alfonso,Norberto Ortego Centeno,Adela Marín Ballvé,José Luis Callejas Rubio,Vicent Fonollosa Plá, Patricia Fanlo

Clinical and experimental rheumatology（2023）

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摘要

This external clinical validation suggests that this algorithm is useful to assist in the diagnosis and follow-up of SSc or RP patients in a timely manner. It may also be helpful in the management of patients with any pathology presenting with microvascular changes, as the algorithm has been designed to also be useful for research aiming at extending the usage of nailfold capillaroscopy to more conditions.

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关键词

nailfold videocapillaroscopy, deep learning, machine learning, systemic sclerosis, Raynaud's phenomenon, algorithm, quantitative

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