Paper · 29401044

Machine Learning Approaches for Clinical Psychology and Psychiatry.

Dwyer DB and 2 others. Annu Rev Clin Psychol, 2018. Cited by 577 papers, by iCite.

11 sourcespapers-2026-11-12-0.1.0

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ConductScience Library. Machine Learning Approaches for Clinical Psychology and Psychiatry. Papers, record 29401044. Release papers-2026-11-12-0.1.0, 12 Nov 2026. https://conductscience.org/library/papers/29401044

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Paper

PubMed's record of the paper, with iCite's citation figures. No abstract is shown.

Title: Machine Learning Approaches for Clinical Psychology and Psychiatry.; PubMed
Journal: Annu Rev Clin Psychol; PubMed
Year: 2018; PubMed
Publication types: Journal Article, Research Support, Non-U.S. Gov't, Review; PubMed
PubMed: https://pubmed.ncbi.nlm.nih.gov/29401044/; PubMed
DOI: https://doi.org/10.1146/annurev-clinpsy-032816-045037; PubMed
The journal: https://conductscience.org/library/journal-index/101235325; PubMed
Citations, by iCite: 577; iCite
Relative citation ratio, by iCite: 31.7; iCite
Revised in PubMed: 2019-07-17; PubMed

Authors3

The authors in the order PubMed's record lists them, with the ORCID iDs it states.

Order	Author	Forename
1	Dwyer DB	Dominic B
2	Falkai P	Peter
3	Koutsouleris N	Nikolaos

Source PubMed

Topics6

NLM's MeSH indexing of the paper, its major topics first.

MeSH term	Major
Machine Learning	Major topic
Mental Disorders	Major topic
Precision Medicine	Major topic
Psychiatry	Major topic
Psychology, Clinical	Major topic
Humans

Source PubMed

Grants0

Each grant PubMed's record writes, matched to the NIH project NIH's grant and paper links name for this paper, and each of those links the record does not write.

None in this release.

Trials0

The trials whose ClinicalTrials.gov record lists the paper, and the trial numbers the paper's PubMed record names.

None in this release.

Comments and corrections0

PubMed's comments and corrections, NLM's own indexing: retractions first, then expressions of concern, errata and updates, and comments last.

None in this release.

References0

The papers the reference list in PubMed's record names, those in our copy of PubMed, in the list's order.

None in this release.

Cited by383

The papers in our copy of PubMed whose reference list names this one, newest first. iCite, which reads more sources, counts 577 citations.

PMID	Title	Journal	Year	In Papers	Source
42,966,759	Can neuroimaging unlock precision therapeutics in psychosis spectrum disorders?	Schizophrenia (Heidelb)	2026	https://conductscience.org/library/papers/42966759	PubMed
42,935,984	Relational representations in classification: comparing similarity and structure-based approaches.	Front Psychol	2026	https://conductscience.org/library/papers/42935984	PubMed
42,928,073	Machine learning for early detection and mood shift prediction in bipolar disorder: a systematic review.	Int J Bipolar Disord	2026	https://conductscience.org/library/papers/42928073	PubMed
42,921,351	CART machine learning peeling pathways for anxiety and depression severity classification in population screening.	Glob Epidemiol	2026	https://conductscience.org/library/papers/42921351	PubMed
42,898,696	Mapping risk of gambling disorder in older adults: a neural network approach.	Front Psychiatry	2026	https://conductscience.org/library/papers/42898696	PubMed
42,881,754	Concurrent Associations of Gaming Time and Problematic Gaming with Depressive Symptoms in Children and Adolescents: A Three-Wave Cohort Study with Complementary Machine Learning Classification.	Healthcare (Basel)	2026	https://conductscience.org/library/papers/42881754	PubMed
42,856,687	Multivariate neural signatures of worry become more differentiated across adolescence and young adulthood: An ultra-high field (7T) fMRI study.	medRxiv	2026	https://conductscience.org/library/papers/42856687	PubMed
42,856,482	Machine-learning classification of documented pedophilic sexual interest from eye-tracking patterns.	Res Sq	2026	https://conductscience.org/library/papers/42856482	PubMed
42,840,883	Cross-Disease Classification of Depression, Bipolar Disorder, and Schizophrenia Using Multiscale Spatiotemporal Network Fusion Features From fNIRS.	Depress Anxiety	2026	https://conductscience.org/library/papers/42840883	PubMed
42,810,795	Machine learning methods and schizophrenia spectrum disorders: a scoping review.	BMJ Open	2026	https://conductscience.org/library/papers/42810795	PubMed

1 to 10 of 383

See all 383 cited by

Genes0

The genes the Gene search release ties to the paper: Swiss-Prot's references first, then PubTator's text mining.

None in this release.

Drugs0

The drugs whose trials, in the Pipelines release, list the paper.

None in this release.

Data0

The data bank entries PubMed's record names. Trial numbers are under Trials.

None in this release.

Data dates

The date of each source this release read.

PubMed: 2026-11-06; PubMed
iCite: 2026-11-05; iCite
PMC's ID file: 2026-11-05; PMC's ID file
NIH RePORTER's grant and paper links: 2026-11-01; NIH RePORTER's grant and paper links
Trials: 2026-11-12
Gene search: 2026-11-11
Pipelines: 2026-09-18

Sources 11

ChEMBL, through Open TargetsCC BY-SA 3.0
ClinicalTrials.govNo license stated
HGNCCC0
iCiteCC BY 4.0
NCBI GenePublic domain (US government)
NIH RePORTER's grant and paper linksPublic domain
Open TargetsCC0 1.0
PMC's ID filePublic domain (US government)
PubMedNLM's terms
PubTator 3Public domain
UniProtCC BY 4.0

Each source's terms

ChEMBL, through Open TargetsCC BY-SA 3.0, for the parts from ChEMBL. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
ClinicalTrials.govnone stated
HGNCCC0: https://www.genenames.org/about/license/
iCiteCC BY 4.0
NCBI GeneNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
NIH RePORTER's grant and paper linksPublic domain (NIH RePORTER)
Open TargetsCC0 1.0. Open Targets asks that users cite its latest paper: Buniello et al. 2025, Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery, Nucleic Acids Research 53(D1):D1467, PMID 39657122. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
PMC's ID fileNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
PubMedNLM's terms
PubTator 3Public domain
UniProtCC BY 4.0. UniProt's licence file: "All databases and documents in the UniProt FTP directory may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy." UniProt asks that users cite its latest paper: The UniProt Consortium, UniProt: the Universal Protein Knowledgebase in 2025, Nucleic Acids Research 53:D609-D617, https://doi.org/10.1093/nar/gkae1010. Read on 9 Nov 2026 at https://www.uniprot.org/help/license

ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.

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