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Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs.
Neurology. 2021 Jul 27;97(4):e369-e377. doi: 10.1212/WNL.0000000000012226. Epub 2021 May 19.
2
Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.
N Engl J Med. 2020 Apr 30;382(18):1687-1695. doi: 10.1056/NEJMoa1917130. Epub 2020 Apr 14.
4
Deep Learning System Outperforms Clinicians in Identifying Optic Disc Abnormalities.
J Neuroophthalmol. 2023 Jun 1;43(2):159-167. doi: 10.1097/WNO.0000000000001800. Epub 2023 Feb 1.
5
Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department.
Am J Ophthalmol. 2024 May;261:199-207. doi: 10.1016/j.ajo.2023.10.025. Epub 2023 Nov 4.
6
A Deep Learning Approach for Accurate Discrimination Between Optic Disc Drusen and Papilledema on Fundus Photographs.
J Neuroophthalmol. 2024 Dec 1;44(4):454-461. doi: 10.1097/WNO.0000000000002223. Epub 2024 Aug 2.
7
Optic Disc Classification by Deep Learning versus Expert Neuro-Ophthalmologists.
Ann Neurol. 2020 Oct;88(4):785-795. doi: 10.1002/ana.25839. Epub 2020 Aug 7.
8
Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.
JAMA Ophthalmol. 2019 Dec 1;137(12):1353-1360. doi: 10.1001/jamaophthalmol.2019.3501.
9
A Deep Learning System for Automated Quality Evaluation of Optic Disc Photographs in Neuro-Ophthalmic Disorders.
Diagnostics (Basel). 2023 Jan 3;13(1):160. doi: 10.3390/diagnostics13010160.
10
Artificial Intelligence to Differentiate Pediatric Pseudopapilledema and True Papilledema on Fundus Photographs.
Ophthalmol Sci. 2024 Feb 20;4(4):100496. doi: 10.1016/j.xops.2024.100496. eCollection 2024 Jul-Aug.

引用本文的文献

1
Detecting papilloedema as a marker of raised intracranial pressure using artificial intelligence: A systematic review.
PLOS Digit Health. 2025 Sep 2;4(9):e0000783. doi: 10.1371/journal.pdig.0000783. eCollection 2025 Sep.
2
WHA-Net: A Low-Complexity Hybrid Model for Accurate Pseudopapilledema Classification in Fundus Images.
Bioengineering (Basel). 2025 May 21;12(5):550. doi: 10.3390/bioengineering12050550.
3
Recent advances in neuro-ophthalmology.
Indian J Ophthalmol. 2024 Nov 1;72(11):1544-1559. doi: 10.4103/IJO.IJO_594_24. Epub 2024 Oct 26.
4
Application of Artificial Intelligence in the Headache Field.
Curr Pain Headache Rep. 2024 Oct;28(10):1049-1057. doi: 10.1007/s11916-024-01297-5. Epub 2024 Jul 8.
5
Classifying and quantifying changes in papilloedema using machine learning.
BMJ Neurol Open. 2024 Jun 26;6(1):e000503. doi: 10.1136/bmjno-2023-000503. eCollection 2024.
6
Diagnostic dilemma of papilledema and pseudopapilledema.
Int Ophthalmol. 2024 Jun 25;44(1):272. doi: 10.1007/s10792-024-03215-5.
8
Deep learning-based optic disc classification is affected by optic-disc tilt.
Sci Rep. 2024 Jan 4;14(1):498. doi: 10.1038/s41598-023-50256-4.
9
The use of artificial intelligence in detecting papilledema from fundus photographs.
Taiwan J Ophthalmol. 2023 Jun 1;13(2):184-190. doi: 10.4103/tjo.TJO-D-22-00178. eCollection 2023 Apr-Jun.

本文引用的文献

1
Optic Disc Classification by Deep Learning versus Expert Neuro-Ophthalmologists.
Ann Neurol. 2020 Oct;88(4):785-795. doi: 10.1002/ana.25839. Epub 2020 Aug 7.
2
An Update on Imaging in Idiopathic Intracranial Hypertension.
Front Neurol. 2020 Jun 10;11:453. doi: 10.3389/fneur.2020.00453. eCollection 2020.
3
Etiology of Papilledema in Patients in the Eye Clinic Setting.
JAMA Netw Open. 2020 Jun 1;3(6):e206625. doi: 10.1001/jamanetworkopen.2020.6625.
4
Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.
N Engl J Med. 2020 Apr 30;382(18):1687-1695. doi: 10.1056/NEJMoa1917130. Epub 2020 Apr 14.
5
Feasibility of a Nonmydriatic Ocular Fundus Camera in an Outpatient Neurology Clinic.
Neurologist. 2020 Mar;25(2):19-23. doi: 10.1097/NRL.0000000000000259.
6
Presentation and Progression of Papilledema in Cerebral Venous Sinus Thrombosis.
Am J Ophthalmol. 2020 May;213:1-8. doi: 10.1016/j.ajo.2019.12.022. Epub 2020 Jan 9.
7
Artificial intelligence for detection of optic disc abnormalities.
Curr Opin Neurol. 2020 Feb;33(1):106-110. doi: 10.1097/WCO.0000000000000773.
8
Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices.
NPJ Digit Med. 2018 Aug 28;1:39. doi: 10.1038/s41746-018-0040-6. eCollection 2018.
9
Idiopathic intracranial hypertension: Proposal of a stratification strategy for monitoring risk of disease progression.
Clin Neurol Neurosurg. 2019 Apr;179:35-41. doi: 10.1016/j.clineuro.2019.02.013. Epub 2019 Feb 15.
10
Predictive role of presenting symptoms and clinical findings in idiopathic intracranial hypertension.
J Neurol Sci. 2019 Apr 15;399:89-93. doi: 10.1016/j.jns.2019.02.006. Epub 2019 Feb 6.

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