The New England journal of medicine, 2020-04, Vol.382 (18), p.1687-1695
- 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
2020
Volltextzugriff (PDF)
Details
- Autor(en) / Beteiligte
- 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
- Titel
- Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs
- Ist Teil von
- The New England journal of medicine, 2020-04, Vol.382 (18), p.1687-1695
- Ort / Verlag
- United States: Massachusetts Medical Society
- Erscheinungsjahr
- 2020
- Quelle
- MEDLINE
- Beschreibungen/Notizen
- 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.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 0028-4793eISSN: 1533-4406DOI: 10.1056/NEJMoa1917130Titel-ID: cdi_proquest_journals_2396354284
- Format
- –
- Schlagworte
- Algorithms, Area Under Curve, Artificial intelligence, Cameras, Classification, Consortia, Datasets, Datasets as Topic, Deep Learning, Diabetic retinopathy, Diagnosis, Differential, Fundus Oculi, Humans, Hypertension, Medical personnel, Medical records, Medical research, Neural Networks, Computer, Ophthalmoscopy - methods, Optic nerve, Papilledema - diagnosis, Patients, Photography, Predictive Value of Tests, Retina - diagnostic imaging, Retina - pathology, Retrospective Studies, ROC Curve, Sensitivity and Specificity, Swelling