Luciano
Boquete Vázquez
Catedrático/a de Universidad
Universidad de Zaragoza
Zaragoza, EspañaPublicacions en col·laboració amb investigadors/es de Universidad de Zaragoza (12)
2024
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Diagnosis of multiple sclerosis using optical coherence tomography supported by explainable artificial intelligence
Eye (Basingstoke), Vol. 38, Núm. 8, pp. 1502-1508
2023
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Diagnosis of multiple sclerosis using optical coherence tomography supported by artificial intelligence
Multiple Sclerosis and Related Disorders, Vol. 74
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Differential Study of Retinal Thicknesses in the Eyes of Alzheimer’s Patients, Multiple Sclerosis Patients and Healthy Subjects
Biomedicines, Vol. 11, Núm. 12
2022
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Objective diagnosis of fibromyalgia using neuroretinal evaluation and artificial intelligence
International journal of clinical and health psychology, Vol. 22, Núm. 2, pp. 31-40
2021
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Automatic diagnosis of bipolar disorder using optical coherence tomography data and artificial intelligence
Journal of Personalized Medicine, Vol. 11, Núm. 8
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Diagnosis of multiple sclerosis using multifocal ERG data feature fusion
Information Fusion, Vol. 76, pp. 157-167
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Early diagnosis of multiple sclerosis by OCT analysis using Cohen's d method and a neural network as classifier
Computers in Biology and Medicine, Vol. 129
2020
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Diagnóstico de esclerosis múltiple mediante el análisis de imágenes de tomografía de coherencia óptica con redes neuronales convolucionales
XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica. CASEIB 2020: Libro de actas
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Empirical mode decomposition-based filter applied to multifocal electroretinograms in multiple sclerosis diagnosis
Sensors (Switzerland), Vol. 20, Núm. 1
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Identification of clusters in multifocal electrophysiology recordings to maximize discriminant capacity (patients vs. control subjects)
Documenta Ophthalmologica, Vol. 140, Núm. 1, pp. 43-53
2019
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Computer-aided diagnosis of multiple sclerosis using a support vector machine and optical coherence tomography features
Sensors (Switzerland), Vol. 19, Núm. 23
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Diagnostic ability of multifocal electroretinogram in early multiple sclerosis using a new signal analysis method
PLoS ONE, Vol. 14, Núm. 11