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Determining Electroconvulsive Therapy Response With Machine Learning
Abbott, Christopher C.1; Loo, Dyani1; Sui, Jing2,3
Source PublicationJAMA PSYCHIATRY
2016-06-01
Volume73Issue:6Pages:545-546
SubtypeEditorial Material
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1001/jamapsychiatry.2016.0348
WOS KeywordDEPRESSION ; BRAIN
Indexed BySCI ; SSCI
Language英语
WOS Research AreaPsychiatry
WOS SubjectPsychiatry
WOS IDWOS:000378868100001
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12039
Collection脑网络组研究中心
Affiliation1.Univ New Mexico, Sch Med, Dept Psychiat, 1101 Yale Blvd,Mail Stop Code 11 6035, Albuquerque, NM 87131 USA
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
3.Mind Res Network, Albuquerque, NM USA
Recommended Citation
GB/T 7714
Abbott, Christopher C.,Loo, Dyani,Sui, Jing. Determining Electroconvulsive Therapy Response With Machine Learning[J]. JAMA PSYCHIATRY,2016,73(6):545-546.
APA Abbott, Christopher C.,Loo, Dyani,&Sui, Jing.(2016).Determining Electroconvulsive Therapy Response With Machine Learning.JAMA PSYCHIATRY,73(6),545-546.
MLA Abbott, Christopher C.,et al."Determining Electroconvulsive Therapy Response With Machine Learning".JAMA PSYCHIATRY 73.6(2016):545-546.
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