Please use this identifier to cite or link to this item: https://doi.org/10.1212/WNL.0000000000012226
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dc.titleAccuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs
dc.contributor.authorVasseneix, Caroline
dc.contributor.authorNajjar, Raymond P
dc.contributor.authorXu, Xinxing
dc.contributor.authorTang, Zhiqun
dc.contributor.authorLoo, Jing Liang
dc.contributor.authorSinghal, Shweta
dc.contributor.authorTow, Sharon
dc.contributor.authorMilea, Leonard
dc.contributor.authorTing, Daniel Shu Wei
dc.contributor.authorLiu, Yong
dc.contributor.authorWong, Tien Y
dc.contributor.authorNewman, Nancy J
dc.contributor.authorBiousse, Valerie
dc.contributor.authorMilea, Dan
dc.date.accessioned2021-12-15T08:45:49Z
dc.date.available2021-12-15T08:45:49Z
dc.date.issued2021-07-27
dc.identifier.citationVasseneix, Caroline, Najjar, Raymond P, Xu, Xinxing, Tang, Zhiqun, Loo, Jing Liang, Singhal, Shweta, Tow, Sharon, Milea, Leonard, Ting, Daniel Shu Wei, Liu, Yong, Wong, Tien Y, Newman, Nancy J, Biousse, Valerie, Milea, Dan (2021-07-27). Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs. NEUROLOGY 97 (4) : E369-E377. ScholarBank@NUS Repository. https://doi.org/10.1212/WNL.0000000000012226
dc.identifier.issn00283878
dc.identifier.issn1526632X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/210599
dc.description.abstractOBJECTIVE: To evaluate the performance of a deep learning system (DLS) in classifying the severity of papilledema associated with increased intracranial pressure on standard retinal fundus photographs. METHODS: A DLS was trained to automatically classify papilledema severity in 965 patients (2,103 mydriatic fundus photographs), representing a multiethnic cohort of patients with confirmed elevated intracranial pressure. Training was performed on 1,052 photographs with mild/moderate papilledema (MP) and 1,051 photographs with severe papilledema (SP) classified by a panel of experts. The performance of the DLS and that of 3 independent neuro-ophthalmologists were tested in 111 patients (214 photographs, 92 with MP and 122 with SP) by calculating the area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, and specificity. Kappa agreement scores between the DLS and each of the 3 graders and among the 3 graders were calculated. RESULTS: The DLS successfully discriminated between photographs of MP and SP, with an AUC of 0.93 (95% confidence interval [CI] 0.89-0.96) and an accuracy, sensitivity, and specificity of 87.9%, 91.8%, and 86.2%, respectively. This performance was comparable with that of the 3 neuro-ophthalmologists (84.1%, 91.8%, and 73.9%, p = 0.19, p = 1, p = 0.09, respectively). Misclassification by the DLS was mainly observed for moderate papilledema (Frisén grade 3). Agreement scores between the DLS and the neuro-ophthalmologists' evaluation was 0.62 (95% CI 0.57-0.68), whereas the intergrader agreement among the 3 neuro-ophthalmologists was 0.54 (95% CI 0.47-0.62). CONCLUSIONS: Our DLS accurately classified the severity of papilledema on an independent set of mydriatic fundus photographs, achieving a comparable performance with that of independent neuro-ophthalmologists. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that a DLS using mydriatic retinal fundus photographs accurately classified the severity of papilledema associated in patients with a diagnosis of increased intracranial pressure.
dc.language.isoen
dc.publisherLIPPINCOTT WILLIAMS & WILKINS
dc.sourceElements
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectClinical Neurology
dc.subjectNeurosciences & Neurology
dc.subjectIDIOPATHIC INTRACRANIAL HYPERTENSION
dc.subjectOPTICAL COHERENCE TOMOGRAPHY
dc.subjectVISUAL-LOSS
dc.subjectCEREBRI
dc.subjectFEASIBILITY
dc.subjectCAMERA
dc.subjectRISK
dc.typeArticle
dc.date.updated2021-12-15T07:48:05Z
dc.contributor.departmentDUKE-NUS OFFICE OF ACAD & CLINICAL DEVT
dc.description.doi10.1212/WNL.0000000000012226
dc.description.sourcetitleNEUROLOGY
dc.description.volume97
dc.description.issue4
dc.description.pageE369-E377
dc.published.statePublished
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