Into the bowels of depression: Unravelling medical symptoms associated with depression by applying machine-learning techniques to a community based population sample
Version 3 2024-06-17, 21:59
Version 2 2024-06-06, 09:26
Version 1 2016-12-01, 00:00
journal contribution
posted on 2024-06-17, 21:59 authored by JF Dipnall, Julie PascoJulie Pasco, Michael BerkMichael Berk, Lana WilliamsLana Williams, Seetal DoddSeetal Dodd, Felice JackaFelice Jacka, D MeyerInto the bowels of depression: Unravelling medical symptoms associated with depression by applying machine-learning techniques to a community based population sample
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United StatesOpen access
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EnglishPublication classification
C Journal article, C1 Refereed article in a scholarly journalCopyright notice
2016, The AuthorsJournal
PLoS ONEVolume
11Season
Article Number : e0167055Article number
ARTN e0167055ISSN
1932-6203eISSN
1932-6203Issue
12Publisher
PUBLIC LIBRARY SCIENCEUsage metrics
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No categories selectedKeywords
Science & TechnologyMultidisciplinary SciencesScience & Technology - Other TopicsLOGISTIC-REGRESSIONDIETARY PATTERNSGUTMICROBIOMEMECHANISMSDISORDERSHEALTHIMPACTSchool of Medicine920410 Mental HealthFaculty of HealthInnovation in Mental and Physical Health and Clinical TreatmentMD Multidisciplinary110999 Neurosciences not elsewhere classified3209 Neurosciences3202 Clinical sciences420313 Mental health services200409 Mental health
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