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Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals.

, , , , , , , , and . Sensors, 20 (11): 3032 (2020)

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Unsupervised Learning as a Complement to Convolutional Neural Network Classification in the Analysis of Saccadic Eye Movement in Spino-Cerebellar Ataxia Type 2., , , , , , , and . IWANN (2), volume 11507 of Lecture Notes in Computer Science, page 26-37. Springer, (2019)Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals., , , , , , , , and . Sensors, 20 (11): 3032 (2020)Cluster Analysis of Finger-to-nose Test for Spinocerebellar Ataxia Assessment., , , , , , and . IWANN (2), volume 9095 of Lecture Notes in Computer Science, page 524-535. Springer, (2015)Selection of Wavelet Decomposition Level for Electro-Oculographic Saccadic De-noising., , , , and . IWANN (2), volume 7903 of Lecture Notes in Computer Science, page 135-141. Springer, (2013)Convolutional Neural Networks for Segmenting Cerebellar Fissures from Magnetic Resonance Imaging., , , and . Sensors, 22 (4): 1345 (2022)ConvNets for automatic detection of polyglutamine SCAs from brain MRIs: state of the art applications., , , and . Medical Biol. Eng. Comput., 61 (1): 1-24 (2023)Convolutional Neural Networks as Support Tools for Spinocerebellar Ataxia Detection from Magnetic Resonances., , and . IWAIPR, volume 13055 of Lecture Notes in Computer Science, page 103-114. Springer, (2021)64-Channel UWB Wireless Neural Vector Analyzer SOC With a Closed-Loop Phase Synchrony-Triggered Neurostimulator., , , , and . IEEE J. Solid State Circuits, 48 (10): 2494-2510 (2013)Closed-Loop Neurostimulators: A Survey and A Seizure-Predicting Design Example for Intractable Epilepsy Treatment., , , , , , and . IEEE Trans. Biomed. Circuits Syst., 11 (5): 1026-1040 (2017)Gap junctions are needed to stabilize slow bursting behaviour., , , and . Neurocomputing, (1999)