Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor
Version 2 2024-06-06, 02:47
Version 1 2022-01-01, 00:00
journal contribution
posted on 2024-06-06, 02:47 authored by T Ngo, DC Nguyen, Pubudu PathiranaPubudu Pathirana, LA Corben, MB Delatycki, M Horne, DJ Szmulewicz, M RobertsFederated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor
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Piscataway, N.J.Link to full text
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EnglishPublication classification
C1 Refereed article in a scholarly journalJournal
IEEE Transactions on Neural Systems and Rehabilitation EngineeringVolume
30Pagination
803-811ISSN
1534-4320eISSN
1558-0210Publisher
Institute of Electrical and Electronics EngineersUsage metrics
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Keywords
Australiacerebellar ataxia (CA)Cloud computingData modelsDeep learningDeep learning (DL)EngineeringEngineering, BiomedicalFeature extractionfederated learning (FL)FRIEDREICH ATAXIAImage sensorsLife Sciences & BiomedicineQUANTITATIVE ASSESSMENTRehabilitationScience & TechnologySensorsTechnologytransfer learning4003 Biomedical engineering
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