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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Multimodal Data Integration Advances Longitudinal Prediction of the Naturalistic Course of Depression and Reveals a Multimodal Signature of Remission During 2-Year Follow-up
Philippe C. Habets, Rajat M. Thomas, Yuri Milaneschi, et al.
Biological Psychiatry (2023) Vol. 94, Iss. 12, pp. 948-958
Open Access | Times Cited: 12

Showing 12 citing articles:

Machine learning-based prediction of illness course in major depression: The relevance of risk factors
Lea Teutenberg, Frederike Stein, Florian Thomas‐Odenthal, et al.
Journal of Affective Disorders (2025)
Closed Access
Predicting incident cardio-metabolic disease among persons with and without depressive and anxiety disorders: a machine learning approach
Arja O. Rydin, George Aalbers, Wessel A. van Eeden, et al.
Social Psychiatry and Psychiatric Epidemiology (2025)
Open Access
Applications of Multimodal Artificial Intelligence in Non-Hodgkin Lymphoma B Cells
Pouria Isavand, Sara Sadat Aghamiri, Rada Amin
Biomedicines (2024) Vol. 12, Iss. 8, pp. 1753-1753
Open Access | Times Cited: 3
Dysconnectivity of the brain functional network and abnormally expressed peripheral transcriptional profiles in patients with anxious depression
Jinxue Wei, Min Wang, Yikai Dou, et al.
Journal of Psychiatric Research (2024) Vol. 171, pp. 316-324
Open Access | Times Cited: 2
Building machine learning prediction models for well-being using predictors from the exposome and genome in a population cohort
Dirk H. M. Pelt, Philippe C. Habets, Christiaan H. Vinkers, et al.
Nature Mental Health (2024) Vol. 2, Iss. 10, pp. 1217-1230
Open Access | Times Cited: 2
Temporal associations between salivary cortisol and emotions in clinically depressed individuals and matched controls: A dynamic time warp analysis
Anne-Sophie C.A.M. Koning, Sanne H. Booij, Onno C. Meijer, et al.
Psychoneuroendocrinology (2023) Vol. 158, pp. 106394-106394
Open Access | Times Cited: 4
The researcher's guide to selecting biomarkers in mental health studies
Josine E. Verhoeven, Owen M. Wolkowitz, Isaac Barr Satz, et al.
BioEssays (2024) Vol. 46, Iss. 10
Open Access | Times Cited: 1
Leveraging Stacked Classifiers for Multi-task Executive Function in Schizophrenia Yields Diagnostic and Prognostic Insights
Tongyi Zhang, Xin Zhao, B.T. Thomas Yeo, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Advancing Clinical Psychiatry: Integration of Clinical and Omics Data Using Machine Learning
Bill Qi, Yannis Trakadis
Biological Psychiatry (2023) Vol. 94, Iss. 12, pp. 908-909
Closed Access | Times Cited: 2
Sex-differential markers of psychiatric risk and treatment response based on premature aging of functional brain network dynamics and peripheral physiology
Raluca Petrican, Sidhant Chopra, Chris Murgatroyd, et al.
Biological Psychiatry (2024)
Open Access
Building machine learning prediction models for wellbeing using predictors from the exposome and genome in a population cohort
Dirk H. M. Pelt, Philippe C. Habets, Christiaan H. Vinkers, et al.
(2023)
Open Access | Times Cited: 1
Table of Contents
Kelsey Hagan, Ella Tian, Tulip Marawi, et al.
Biological Psychiatry (2023) Vol. 94, Iss. 12, pp. A3-A4
Open Access
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