Deep Learning outperforms physicians in myopathy and neuropathy classification based on Needle Electromyography Signal.
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| Title: | Deep Learning outperforms physicians in myopathy and neuropathy classification based on Needle Electromyography Signal. |
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| Authors: | Yoo I; Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Nowon-gu, Seoul, Republic of Korea., Yoo J; School of Electrical Engineering, Korea University, Seongbuk-gu, Seoul, Republic of Korea., Kim D; Biomedical Research Institute, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Youn I; Department of Computer Science, New York University, New York, New York, United States of America., Kim H; Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Nowon-gu, Seoul, Republic of Korea., Youn M; Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Nowon-gu, Seoul, Republic of Korea., Won JH; Department of Rehabilitation Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Cho W; Department of Rehabilitation Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Myong Y; Department of Rehabilitation Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Kim S; Department of Rehabilitation Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Yu R; Department of Rehabilitation Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Kim SM; Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Jongno-gu, Seoul, Republic of Korea., Kim K; Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea., Lee SB; Department of Medical Informatics, Keimyung University School of Medicine, Nam-gu, Daegu, Republic of Korea., Kim K; Department of Rehabilitation Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Republic of Korea.; Office of Vision, Seoul National University College of Medicine, Jongno-gu, Seoul, Republic of Korea. |
| Source: | PloS one [PLoS One] 2026 May 19; Vol. 21 (5), pp. e0339691. Date of Electronic Publication: 2026 May 19 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0339691 |
