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Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data

Biological Psychiatry Cognitive Neuroscience and Neuroimaging(2021)10.1016/j.bpsc.2021.03.005Source: DataRank Database

Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data is a research paper published in Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2021). On theSindex it has a DataRank of 0. It has been cited 35 times.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (40 grants)OA: bronzeTopics (14)IDs (PubMed)

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Findable (1/2)

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Accessible (1/2)

Open Access

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Reusable (0/3)

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Authors (35)

Akhil Kottaram ORCID,Richard Dinga ORCID,Christopher G. Davey ORCID,Tobias Banaschewski ORCID,Arun L.W. Bokde ORCID

Live enrichment

PubMed:33753312

Bundesministerium für Bildung und Forschung

Grant: AERIAL 01EE1406A

Bundesministerium für Bildung und Forschung

Grant: 01EV0711

Bundesministerium für Bildung und Forschung

Grant: 01EE1406B

Bundesministerium für Bildung und Forschung

Grant: 01GL1745B

Bundesministerium für Bildung und Forschung

Grant: 01GS08152

NIH

Grant: 1R56AG058854-01

NIH

Grant: R01MH117601

NIH

Grant: R01DA049238

NIH

Grant: U54 EB020403

Fondation de l'Avenir

Grant: AP-RM-17-013

Science Foundation Ireland

Grant: 16/ERCD/3797

Deutsche Forschungsgemeinschaft

Grant: NE 1383/14-1

Deutsche Forschungsgemeinschaft

Grant: SM 80/7-2

Deutsche Forschungsgemeinschaft

Grant: SFB 940

Deutsche Forschungsgemeinschaft

Grant: TRR 265

Fondation pour la Recherche Medicale

Grant: DPA20140629802

ANR

Grant: ANR-12-SAMA-0004

NHMRC

Grant: 141738

NHMRC

Grant: 1140764

Fondation de France

Grant: 00081242

Sixth Framework Programme

Grant: LSHM-CT-2007-037286

Horizon 2020

Grant: 785907

Horizon 2020

Grant: 945539

Horizon 2020

Grant: 695313

Medical Research Council

Grant: MR/N000390/1

Medical Research Foundation

Grant: MRF-058-0004-RG-DESRI

Medical Research Council

Grant: MR/S020306/1

Medical Research Council

Grant: MR/R00465X/1

MRF_

Grant: MRF-058-0009-RG-DESR-C0759

National Institutes of Health

Grant: 5U54EB020403-05

NIA NIH HHS

Grant: R56 AG058854

Bundesministerium für Bildung und Forschung

Institut National de la Santé et de la Recherche Médicale

National Institute for Health Research (NIHR)

National Institute of Mental Health

Université Paris-Sud

Deutsche Forschungsgemeinschaft

European Commission

King’s College London

Fédération pour la Recherche sur le Cerveau

bronzeLicense: cc-by-nc-nd

publisherhttps://www.sciencedirect.com/science/article/am/pii/S2451902221000823?via%3Dihub

publisherhttps://api.elsevier.com/content/article/PII:S2451902221000823?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2451902221000823?httpAccept=text/plain

repositoryhttps://nottingham-repository.worktribe.com/output/5722414

repositoryhttp://hdl.handle.net/1887/3513632

MeSH Terms

HumansRisk FactorsLongitudinal StudiesDepressionCognitionAdolescentFemaleMajor Depressive Disorder

Keywords

PredictionDepressionAdolescentsMachine LearningMajor Depressive DisorderPenalized Logistic Regression