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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:

Predicting Suicidal Behavior From Longitudinal Electronic Health Records
Yuval Barak‐Corren, Víctor M. Castro, Solomon Javitt, et al.
American Journal of Psychiatry (2016) Vol. 174, Iss. 2, pp. 154-162
Open Access | Times Cited: 309

Showing 1-25 of 309 citing articles:

Prediction Models for Suicide Attempts and Deaths
Bradley E. Belsher, Derek J. Smolenski, Larry D. Pruitt, et al.
JAMA Psychiatry (2019) Vol. 76, Iss. 6, pp. 642-642
Closed Access | Times Cited: 411
Improving Suicide Prevention Through Evidence-Based Strategies: A Systematic Review
J. John Mann, Christina A. Michel, Randy P. Auerbach
American Journal of Psychiatry (2021) Vol. 178, Iss. 7, pp. 611-624
Open Access | Times Cited: 357
Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records
Gregory E. Simon, Eric Johnson, Jean M. Lawrence, et al.
American Journal of Psychiatry (2018) Vol. 175, Iss. 10, pp. 951-960
Open Access | Times Cited: 328
Characterisation of mental health conditions in social media using Informed Deep Learning
George Gkotsis, Anika Oellrich, Sumithra Velupillai, et al.
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 211
Severity and Variability of Depression Symptoms Predicting Suicide Attempt in High-Risk Individuals
Nadine Melhem, Giovanna Porta, María A. Oquendo, et al.
JAMA Psychiatry (2019) Vol. 76, Iss. 6, pp. 603-603
Open Access | Times Cited: 209
Suicide prediction models: a critical review of recent research with recommendations for the way forward
Ronald C. Kessler, Robert M. Bossarte, Alex Luedtke, et al.
Molecular Psychiatry (2019) Vol. 25, Iss. 1, pp. 168-179
Open Access | Times Cited: 169
Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, and Electronic Health Records
Matthew K. Nock, Alexander J. Millner, Eric L. Ross, et al.
JAMA Network Open (2022) Vol. 5, Iss. 1, pp. e2144373-e2144373
Open Access | Times Cited: 109
Machine learning model to predict mental health crises from electronic health records
Roger Garriga, Javier Mas, Semhar Abraha, et al.
Nature Medicine (2022) Vol. 28, Iss. 6, pp. 1240-1248
Open Access | Times Cited: 100
Using Machine Learning to Predict Complications in Pregnancy: A Systematic Review
Ayleen Bertini, Rodrigo Salas, Stéren Chabert, et al.
Frontiers in Bioengineering and Biotechnology (2022) Vol. 9
Open Access | Times Cited: 87
Identifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing
Andrea Fernandes, Rina Dutta, Sumithra Velupillai, et al.
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 153
A survey on big data-driven digital phenotyping of mental health
Yunji Liang, Xiaolong Zheng, Daniel Zeng
Information Fusion (2019) Vol. 52, pp. 290-307
Closed Access | Times Cited: 134
Machine learning in suicide science: Applications and ethics
Kathryn P. Linthicum, Katherine Musacchio Schafer, Jessica D. Ribeiro
Behavioral Sciences & the Law (2019) Vol. 37, Iss. 3, pp. 214-222
Closed Access | Times Cited: 130
Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark
Jaimie L. Gradus, Anthony J. Rosellini, Erzsébet Horváth‐Puhó, et al.
JAMA Psychiatry (2019) Vol. 77, Iss. 1, pp. 25-25
Open Access | Times Cited: 121
Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide
Douglas M. Ruderfer, Colin G. Walsh, Matthew Aguirre, et al.
Molecular Psychiatry (2019) Vol. 25, Iss. 10, pp. 2422-2430
Open Access | Times Cited: 120
Advancing the Understanding of Suicide: The Need for Formal Theory and Rigorous Descriptive Research
Alexander J. Millner, Donald J. Robinaugh, Matthew K. Nock
Trends in Cognitive Sciences (2020) Vol. 24, Iss. 9, pp. 704-716
Open Access | Times Cited: 117
The use of electronic health records for psychiatric phenotyping and genomics
Jordan W. Smoller
American Journal of Medical Genetics Part B Neuropsychiatric Genetics (2017) Vol. 177, Iss. 7, pp. 601-612
Open Access | Times Cited: 116
Understanding suicide risk within the Research Domain Criteria (RDoC) framework: A meta-analytic review
Catherine R. Glenn, Evan M. Kleiman, B. Christine, et al.
Depression and Anxiety (2017) Vol. 35, Iss. 1, pp. 65-88
Open Access | Times Cited: 115
Clinical text classification research trends: Systematic literature review and open issues
Ghulam Mujtaba, Liyana Shuib, Norisma Idris, et al.
Expert Systems with Applications (2018) Vol. 116, pp. 494-520
Closed Access | Times Cited: 114
Clinical Text Mining
Hercules Dalianis
Springer eBooks (2018)
Closed Access | Times Cited: 107
Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records
Nicholas Carson, Brian Mullin, María José Sánchez Román, et al.
PLoS ONE (2019) Vol. 14, Iss. 2, pp. e0211116-e0211116
Open Access | Times Cited: 96
Machine learning for suicide risk prediction in children and adolescents with electronic health records
Chang Su, Robert H. Aseltine, Riddhi Doshi, et al.
Translational Psychiatry (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 96
Genome-Wide Association Study of Suicide Death and Polygenic Prediction of Clinical Antecedents
Anna R. Docherty, Andrey A. Shabalin, Emily DiBlasi, et al.
American Journal of Psychiatry (2020) Vol. 177, Iss. 10, pp. 917-927
Open Access | Times Cited: 94
Big Brain Data: On the Responsible Use of Brain Data from Clinical and Consumer-Directed Neurotechnological Devices
Philipp Kellmeyer
Neuroethics (2018) Vol. 14, Iss. 1, pp. 83-98
Open Access | Times Cited: 90
Validation of an Electronic Health Record–Based Suicide Risk Prediction Modeling Approach Across Multiple Health Care Systems
Yuval Barak‐Corren, Víctor M. Castro, Matthew K. Nock, et al.
JAMA Network Open (2020) Vol. 3, Iss. 3, pp. e201262-e201262
Open Access | Times Cited: 87
Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records
Le Zheng, Oliver Wang, Shiying Hao, et al.
Translational Psychiatry (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 83
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