文献
J-GLOBAL ID:202202211229269944
整理番号:22A1086276
小脳失調症の診断のための連合深層学習:プライバシー保存と自動切断特徴抽出器【JST・京大機械翻訳】
Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor
著者 (8件):
Ngo Thang
(School of Engineering, Deakin University, Waurn Ponds, VIC, Australia)
,
Nguyen Dinh C.
(School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA)
,
Pathirana Pubudu N.
(School of Engineering, Deakin University, Waurn Ponds, VIC, Australia)
,
Corben Louise A.
(Murdoch Children’s Research Institute, Parkville, VIC, Australia)
,
Delatycki Martin B.
(Murdoch Children’s Research Institute, Parkville, VIC, Australia)
,
Horne Malcolm
(Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia)
,
Szmulewicz David J.
(Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia)
,
Roberts Melissa
(Physiotherapy Department, Monash Health, Clayton, VIC, Australia)
資料名:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
(IEEE Transactions on Neural Systems and Rehabilitation Engineering)
巻:
30
ページ:
803-811
発行年:
2022年
JST資料番号:
W0560A
ISSN:
1534-4320
CODEN:
ITNSB3
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)