Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Rosenström, Tom
Elovainio, Marko
Jokela, Markus
Pirkola, Sami
Koskinen, Seppo
Lindfors, Olavi
and
Keltikangas-Järvinen, Liisa
2015.
Concordance between Composite International Diagnostic Interview and self-reports of depressive symptoms: a re-analysis.
International Journal of Methods in Psychiatric Research,
Vol. 24,
Issue. 3,
p.
213.
van Loo, Hanna M.
Aggen, Steven H.
Gardner, Charles O.
and
Kendler, Kenneth S.
2015.
Multiple risk factors predict recurrence of major depressive disorder in women.
Journal of Affective Disorders,
Vol. 180,
Issue. ,
p.
52.
Kessler, R C
van Loo, H M
Wardenaar, K J
Bossarte, R M
Brenner, L A
Cai, T
Ebert, D D
Hwang, I
Li, J
de Jonge, P
Nierenberg, A A
Petukhova, M V
Rosellini, A J
Sampson, N A
Schoevers, R A
Wilcox, M A
and
Zaslavsky, A M
2016.
Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports.
Molecular Psychiatry,
Vol. 21,
Issue. 10,
p.
1366.
ten Have, Margreet
Lamers, Femke
Wardenaar, Klaas
Beekman, Aartjan
de Jonge, Peter
van Dorsselaer, Saskia
Tuithof, Marlous
Kleinjan, Marloes
and
de Graaf, Ron
2016.
The identification of symptom-based subtypes of depression: A nationally representative cohort study.
Journal of Affective Disorders,
Vol. 190,
Issue. ,
p.
395.
van Loo, Hanna M.
Schoevers, Robert A.
Kendler, Kenneth S.
de Jonge, Peter
and
Romeijn, Jan-Willem
2016.
PSYCHIATRIC COMORBIDITY DOES NOT ONLY DEPEND ON DIAGNOSTIC THRESHOLDS: AN ILLUSTRATION WITH MAJOR DEPRESSIVE DISORDER AND GENERALIZED ANXIETY DISORDER.
Depression and Anxiety,
Vol. 33,
Issue. 2,
p.
143.
.Gillan, Claire M
and
Whelan, Robert
2017.
What big data can do for treatment in psychiatry.
Current Opinion in Behavioral Sciences,
Vol. 18,
Issue. ,
p.
34.
Kessler, R. C.
van Loo, H. M.
Wardenaar, K. J.
Bossarte, R. M.
Brenner, L. A.
Ebert, D. D
de Jonge, P.
Nierenberg, A. A.
Rosellini, A. J.
Sampson, N. A.
Schoevers, R. A.
Wilcox, M. A.
and
Zaslavsky, A. M.
2017.
Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder.
Epidemiology and Psychiatric Sciences,
Vol. 26,
Issue. 1,
p.
22.
van Loo, H.M.
Van Borkulo, C.D.
Peterson, R.E.
Fried, E.I.
Aggen, S.H.
Borsboom, D.
and
Kendler, K.S.
2018.
Robust symptom networks in recurrent major depression across different levels of genetic and environmental risk.
Journal of Affective Disorders,
Vol. 227,
Issue. ,
p.
313.
Kautzky, Alexander
Lanzenberger, Rupert
and
Kasper, Siegfried
2019.
Personalized Psychiatry.
p.
53.
Shatte, Adrian B. R.
Hutchinson, Delyse M.
and
Teague, Samantha J.
2019.
Machine learning in mental health: a scoping review of methods and applications.
Psychological Medicine,
Vol. 49,
Issue. 09,
p.
1426.
Paul, Riya
Andlauer, Till. F. M.
Czamara, Darina
Hoehn, David
Lucae, Susanne
Pütz, Benno
Lewis, Cathryn M.
Uher, Rudolf
Müller-Myhsok, Bertram
Ising, Marcus
and
Sämann, Philipp G.
2019.
Treatment response classes in major depressive disorder identified by model-based clustering and validated by clinical prediction models.
Translational Psychiatry,
Vol. 9,
Issue. 1,
van Loo, Hanna M.
Bigdeli, Tim B.
Milaneschi, Yuri
Aggen, Steven H.
and
Kendler, Kenneth S.
2020.
Data mining algorithm predicts a range of adverse outcomes in major depression.
Journal of Affective Disorders,
Vol. 276,
Issue. ,
p.
945.
Ermers, Nick J.
Hagoort, Karin
and
Scheepers, Floortje E.
2020.
The Predictive Validity of Machine Learning Models in the Classification and Treatment of Major Depressive Disorder: State of the Art and Future Directions.
Frontiers in Psychiatry,
Vol. 11,
Issue. ,
Romeijn, Jan-Willem
and
van Loo, Hanna M.
2020.
Levels of Analysis in Psychopathology.
p.
349.
Miché, Marcel
Studerus, Erich
Meyer, Andrea Hans
Gloster, Andrew Thomas
Beesdo-Baum, Katja
Wittchen, Hans-Ulrich
and
Lieb, Roselind
2020.
Prospective prediction of suicide attempts in community adolescents and young adults, using regression methods and machine learning.
Journal of Affective Disorders,
Vol. 265,
Issue. ,
p.
570.
Clark, Shaunna L.
Hattab, Mohammad W.
Chan, Robin F.
Shabalin, Andrey A.
Han, Laura K. M.
Zhao, Min
Smit, Johannes H.
Jansen, Rick
Milaneschi, Yuri
Xie, Lin Ying
van Grootheest, Gerard
Penninx, Brenda W. J. H.
Aberg, Karolina A.
and
van den Oord, Edwin J. C. G.
2020.
A methylation study of long-term depression risk.
Molecular Psychiatry,
Vol. 25,
Issue. 6,
p.
1334.
Vetter, Johannes Simon
Schultebraucks, Katharina
Galatzer-Levy, Isaac
Boeker, Heinz
Brühl, Annette
Seifritz, Erich
and
Kleim, Birgit
2022.
Predicting non-response to multimodal day clinic treatment in severely impaired depressed patients: a machine learning approach.
Scientific Reports,
Vol. 12,
Issue. 1,
Nag, Akash
Sen, Maddhuja
and
Saha, Jyotiraditya
2023.
Predictive Analytics in Cloud, Fog, and Edge Computing.
p.
133.
Pettitt, Adam K.
Nelson, Benjamin W.
Forman‐Hoffman, Valerie L.
Goldin, Philippe R.
and
Peiper, Nicholas C.
2024.
Longitudinal outcomes of a therapist‐supported digital mental health intervention for depression and anxiety symptoms: A retrospective cohort study.
Psychology and Psychotherapy: Theory, Research and Practice,
Vol. 97,
Issue. 2,
p.
288.