Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs

A deep-learning system that was applied to 14,341 fundus photographs differentiated optic disks with papilledema from normal disks with 96.4% sensitivity and 84.7% specificity in an external-testing data set. The prevalence of papilledema was 9.5%, yielding positive and negative predictive values of...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	The New England journal of medicine 2020-04, Vol.382 (18), p.1687-1695
Hauptverfasser:	Milea, Dan, Najjar, Raymond P, Zhubo, Jiang, Ting, Daniel, Vasseneix, Caroline, Xu, Xinxing, Aghsaei Fard, Masoud, Fonseca, Pedro, Vanikieti, Kavin, Lagrèze, Wolf A, La Morgia, Chiara, Cheung, Carol Y, Hamann, Steffen, Chiquet, Christophe, Sanda, Nicolae, Yang, Hui, Mejico, Luis J, Rougier, Marie-Bénédicte, Kho, Richard, Thi Ha Chau, Tran, Singhal, Shweta, Gohier, Philippe, Clermont-Vignal, Catherine, Cheng, Ching-Yu, Jonas, Jost B, Yu-Wai-Man, Patrick, Fraser, Clare L, Chen, John J, Ambika, Selvakumar, Miller, Neil R, Liu, Yong, Newman, Nancy J, Wong, Tien Y, Biousse, Valérie
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Area Under Curve Artificial intelligence Cameras Classification Consortia Datasets Datasets as Topic Deep Learning Diabetic retinopathy Diagnosis, Differential Fundus Oculi General & Internal Medicine Humans Hypertension Life Sciences & Biomedicine Medical personnel Medical records Medical research Medicine, General & Internal Neural Networks, Computer Ophthalmoscopy - methods Optic nerve Papilledema - diagnosis Patients Photography Predictive Value of Tests Retina - diagnostic imaging Retina - pathology Retrospective Studies ROC Curve Science & Technology Sensitivity and Specificity Swelling
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	A deep-learning system that was applied to 14,341 fundus photographs differentiated optic disks with papilledema from normal disks with 96.4% sensitivity and 84.7% specificity in an external-testing data set. The prevalence of papilledema was 9.5%, yielding positive and negative predictive values of 39.8% and 99.6%, respectively.
ISSN:	0028-4793 1533-4406
DOI:	10.1056/NEJMoa1917130