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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 depressive symptoms in middle-aged and elderly adults using sleep data and clinical health markers: A machine learning approach
Stephania Ruth Basílio Silva Gomes, Malcolm von Schantz, Mário André Leocadio-Miguel
Sleep Medicine (2023) Vol. 102, pp. 123-131
Open Access | Times Cited: 14

Showing 14 citing articles:

Depressive symptoms and all-cause mortality among middle-aged and older people in China and associations with chronic diseases
Lan Zhu, Yixi Wang, Jiaqi Li, et al.
Frontiers in Public Health (2024) Vol. 12
Open Access | Times Cited: 7
Machine learning models to predict posttraumatic stress injuries in a sample of firefighters: A proof of concept
Filippo Rapisarda, Marc J. Lanovaz, Stéphane Guay, et al.
International Journal of Mental Health (2025), pp. 1-21
Closed Access
Evaluating Machine Learning Stability in Predicting Depression and Anxiety Amidst Subjective Response Errors
Wai Lim Ku, Hua Min
Healthcare (2024) Vol. 12, Iss. 6, pp. 625-625
Open Access | Times Cited: 4
Machine learning in public health informatics: evidence that complex sampling structures may not be needed for prediction models with imbalanced outcomes.
Zhengye Si, Jinpu Li, Emily Leary
Annals of Epidemiology (2025)
Closed Access
Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms
Zhao Chen, Hao Liu, Yao Zhang, et al.
Frontiers in Public Health (2025) Vol. 13
Open Access
Bayesian networks for feature selection and patient pre-screening for depressive symptomatology: a prototype (Preprint)
Eduardo Maekawa, Eoin Martino Grua, Carina Akemi Nakamura, et al.
JMIR Mental Health (2024) Vol. 11, pp. e52045-e52045
Open Access | Times Cited: 2
Impact of Artificial Intelligence in Nursing for Geriatric Clinical Care for Chronic Diseases: A Systematic Literature Review
Mahdieh Poodineh Moghadam, Zabih Allah Moghadam, Mohammad Reza Chalak Qazani, et al.
IEEE Access (2024) Vol. 12, pp. 122557-122587
Open Access | Times Cited: 2
Major Depressive Disorder Prediction Based on Sleep-Wake Disorders Symptoms in US Adolescents: A Machine Learning Approach from National Sleep Research Resource
Jingsong Luo, Yuxin Chen, Yanmin Tao, et al.
Psychology Research and Behavior Management (2024) Vol. Volume 17, pp. 691-703
Open Access | Times Cited: 1
Chlorogenic Acids, Acting via Calcineurin, Are the Main Compounds in Centella asiatica Extracts That Mediate Resilience to Chronic Stress in Drosophila melanogaster
Helen Holvoet, Dani M. Long, Liping Yang, et al.
Nutrients (2023) Vol. 15, Iss. 18, pp. 4016-4016
Open Access | Times Cited: 3
Evaluating Machine Learning Stability in Predicting Depression and Anxiety Amidst Subjective Response Errors
Wai Lim Ku, Hua Min
(2023)
Open Access | Times Cited: 3
An Intelligent and Effective Framework for Reduction of Diabetes Risk
Amit Kumar Mishra, Neha Tripathi, Ashish Gupta, et al.
(2023), pp. 668-674
Closed Access | Times Cited: 2
Lifestyle factors and other predictors of common mental disorders in diagnostic machine learning studies: A systematic review
Emma Todd, Rebecca Orr, Elizabeth Gamage, et al.
Computers in Biology and Medicine (2024) Vol. 185, pp. 109521-109521
Open Access
Bayesian networks for feature selection and patient screening for depressive symptomatology: Practical applications of machine learning models (Preprint)
Eduardo Maekawa, Eoin Martino Grua, Carina Akemi Nakamura, et al.
(2023)
Closed Access
Correlation Analysis Between Insomnia Severity and Depressive Symptoms of College Students Based on Pseudo-Siamese Network
Ya-fei Wang, Yan-ling Zhu, Peng Wu, et al.
Communications in computer and information science (2023), pp. 116-127
Closed Access
Machine Learning in Diabetes Modeling
Sina Ardabili, Amirhosein Mosavi, Imre Felde
(2023), pp. 000487-000494
Closed Access
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