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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:

Machine learning methods for developing precision treatment rules with observational data
Ronald C. Kessler, Robert M. Bossarte, Alex Luedtke, et al.
Behaviour Research and Therapy (2019) Vol. 120, pp. 103412-103412
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

Supervised Machine Learning: A Brief Primer
Tammy Jiang, Jaimie L. Gradus, Anthony J. Rosellini
Behavior Therapy (2020) Vol. 51, Iss. 5, pp. 675-687
Open Access | Times Cited: 506
A Survey on Causal Inference
Liuyi Yao, Zhixuan Chu, Sheng Li, et al.
ACM Transactions on Knowledge Discovery from Data (2021) Vol. 15, Iss. 5, pp. 1-46
Open Access | Times Cited: 311
Gut microbiome, big data and machine learning to promote precision medicine for cancer
Giovanni Cammarota, Gianluca Ianiro, Anna M. Ahern, et al.
Nature Reviews Gastroenterology & Hepatology (2020) Vol. 17, Iss. 10, pp. 635-648
Closed Access | Times Cited: 242
Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health
Leonard Bickman
Administration and Policy in Mental Health and Mental Health Services Research (2020) Vol. 47, Iss. 5, pp. 795-843
Open Access | Times Cited: 137
Single‐case experimental designs: Characteristics, changes, and challenges
Alan E. Kazdin
Journal of the Experimental Analysis of Behavior (2020) Vol. 115, Iss. 1, pp. 56-85
Closed Access | Times Cited: 96
Prevention of eating disorders at universities: A systematic review and meta‐analysis
Mathias Harrer, Sophia Helen Adam, Eva-Maria Meßner, et al.
International Journal of Eating Disorders (2020) Vol. 53, Iss. 6, pp. 813-833
Open Access | Times Cited: 88
Racism and Poverty are Barriers to the Treatment of Youth Mental Health Concerns
Franckie Castro‐Ramirez, Maha Al‐Suwaidi, Pedro García, et al.
Journal of Clinical Child & Adolescent Psychology (2021) Vol. 50, Iss. 4, pp. 534-546
Closed Access | Times Cited: 80
Targeted prescription of cognitive–behavioral therapy versus person-centered counseling for depression using a machine learning approach.
Jaime Delgadillo, Paulina Gonzalez Salas Duhne
Journal of Consulting and Clinical Psychology (2019) Vol. 88, Iss. 1, pp. 14-24
Open Access | Times Cited: 77
A survey on causal inference for recommendation
Huishi Luo, Fuzhen Zhuang, Ruobing Xie, et al.
The Innovation (2024) Vol. 5, Iss. 2, pp. 100590-100590
Open Access | Times Cited: 15
Post-discharge suicide prediction among US veterans using natural language processing-enriched social and behavioral determinants of health
Avijit Mitra, Kun Chen, Weisong Liu, et al.
npj Mental Health Research (2025) Vol. 4, Iss. 1
Open Access | Times Cited: 1
Pragmatic Precision Psychiatry—A New Direction for Optimizing Treatment Selection
Ronald C. Kessler, Alex Luedtke
JAMA Psychiatry (2021) Vol. 78, Iss. 12, pp. 1384-1384
Closed Access | Times Cited: 55
Predicting patients who will drop out of out-patient psychotherapy using machine learning algorithms
Björn Bennemann, Brian Schwartz, Julia Giesemann, et al.
The British Journal of Psychiatry (2022) Vol. 220, Iss. 4, pp. 192-201
Open Access | Times Cited: 36
Predicting dropout from psychological treatment using different machine learning algorithms, resampling methods, and sample sizes
Julia Giesemann, Jaime Delgadillo, Brian Schwartz, et al.
Psychotherapy Research (2023) Vol. 33, Iss. 6, pp. 683-695
Closed Access | Times Cited: 18
Revolutionizing Kidney Transplantation: Connecting Machine Learning and Artificial Intelligence with Next-Generation Healthcare—From Algorithms to Allografts
Luís Ramalhete, Paula Almeida, Raquel Ferreira, et al.
BioMedInformatics (2024) Vol. 4, Iss. 1, pp. 673-689
Open Access | Times Cited: 6
Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data
Lorenzo Lorenzo‐Luaces, Allison Peipert, Robinson De Jesús Romero, et al.
International Journal of Cognitive Therapy (2020) Vol. 14, Iss. 1, pp. 59-85
Closed Access | Times Cited: 43
Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System
Ronald C. Kessler, Mark S. Bauer, Todd M. Bishop, et al.
Frontiers in Psychiatry (2020) Vol. 11
Open Access | Times Cited: 40
Big data and predictive modelling for the opioid crisis: existing research and future potential
Chrianna Bharat, Matthew Hickman, Sebastiano Barbieri, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 6, pp. e397-e407
Closed Access | Times Cited: 35
One Size Does Not Fit All: A Comprehensive Clinical Approach to Reducing Suicidal Ideation, Attempts, and Deaths
David A. Jobes, Samantha A. Chalker
International Journal of Environmental Research and Public Health (2019) Vol. 16, Iss. 19, pp. 3606-3606
Open Access | Times Cited: 40
Why Are Suicide Rates Increasing in the United States? Towards a Multilevel Reimagination of Suicide Prevention
Gonzalo Martínez‐Alés, Daniel Hernández-Calle, Nicole Khauli, et al.
Current topics in behavioral neurosciences (2020), pp. 1-23
Open Access | Times Cited: 38
Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables
Giampaolo Perna, Alessandra Alciati, Silvia Daccò, et al.
Psychiatry Investigation (2020) Vol. 17, Iss. 3, pp. 193-206
Open Access | Times Cited: 37
Mental health and wellbeing of Australian police and emergency services employees
Michael J. Kyron, Wavne Rikkers, Jennifer Bartlett, et al.
Archives of Environmental & Occupational Health (2021) Vol. 77, Iss. 4, pp. 282-292
Open Access | Times Cited: 29
Predicting early dropout in online versus face-to-face guided self-help: A machine learning approach
Paulina Gonzalez Salas Duhne, Jaime Delgadillo, Wolfgang Lutz
Behaviour Research and Therapy (2022) Vol. 159, pp. 104200-104200
Open Access | Times Cited: 19
Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia
Chi‐Shin Wu, Alex Luedtke, Ekaterina Sadikova, et al.
JAMA Network Open (2020) Vol. 3, Iss. 2, pp. e1921660-e1921660
Open Access | Times Cited: 29
Evaluation of randomized controlled trials: a primer and tutorial for mental health researchers
Mathias Harrer, Pim Cuijpers, Lea Schuurmans, et al.
Trials (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 9
A Survey on Causal Inference
Liuyi Yao, Zhixuan Chu, Sheng Li, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 26
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