Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Classification of Parkinson’s Disease Using Resting-State Hemodynamic Signals and Machine Learning

Full metadata record
DC Field Value Language
dc.contributor.authorKim, Beop-Min-
dc.date.accessioned2021-08-27T21:25:09Z-
dc.date.available2021-08-27T21:25:09Z-
dc.date.created2021-04-22-
dc.date.issued2018-10-07-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/17618-
dc.publisherthe society for functional near infrared spectroscopy-
dc.titleClassification of Parkinson’s Disease Using Resting-State Hemodynamic Signals and Machine Learning-
dc.title.alternativeClassification of Parkinson’s Disease Using Resting-State Hemodynamic Signals and Machine Learning-
dc.typeConference-
dc.contributor.affiliatedAuthorKim, Beop-Min-
dc.identifier.bibliographicCitationfNIRS 2018-
dc.relation.isPartOffNIRS 2018-
dc.relation.isPartOffNIRS 2018-
dc.citation.titlefNIRS 2018-
dc.citation.conferencePlaceJA-
dc.citation.conferenceDate2018-10-05-
dc.type.rimsCONF-
dc.description.journalClass1-
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Bioengineering > 2. Conference Papers

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE