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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:

Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing
Prerna Chikersal, Afsaneh Doryab, Michael Tumminia, et al.
ACM Transactions on Computer-Human Interaction (2021) Vol. 28, Iss. 1, pp. 1-41
Open Access | Times Cited: 100

Showing 1-25 of 100 citing articles:

Modern views of machine learning for precision psychiatry
Zhe Chen, Prathamesh Kulkarni, Isaac R. Galatzer‐Levy, et al.
Patterns (2022) Vol. 3, Iss. 11, pp. 100602-100602
Open Access | Times Cited: 83
Influencing factors, prediction and prevention of depression in college students: A literature review
Xinqiao Liu, Yu-Xin Guo, Wenjie Zhang, et al.
World Journal of Psychiatry (2022) Vol. 12, Iss. 7, pp. 860-873
Open Access | Times Cited: 82
Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression
Alaa Abd‐Alrazaq, Rawan AlSaad, Farag Shuweihdi, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 46
Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches
Lin Sze Khoo, Mei Kuan Lim, Chun Yong Chong, et al.
Sensors (2024) Vol. 24, Iss. 2, pp. 348-348
Open Access | Times Cited: 21
Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis
Kennedy Opoku Asare, Isaac Moshe, Yannik Terhorst, et al.
Pervasive and Mobile Computing (2022) Vol. 83, pp. 101621-101621
Open Access | Times Cited: 55
Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review
Alaa Abd‐Alrazaq, Rawan AlSaad, Sarah Aziz, et al.
Journal of Medical Internet Research (2022) Vol. 25, pp. e42672-e42672
Open Access | Times Cited: 54
GLOBEM
Xuhai Xu, Xin Liu, Han Zhang, et al.
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2022) Vol. 6, Iss. 4, pp. 1-34
Open Access | Times Cited: 47
Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges
Xiaojie Cao, Xinqiao Liu
World Journal of Psychiatry (2022) Vol. 12, Iss. 10, pp. 1287-1297
Open Access | Times Cited: 45
Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study
Tahsin Mullick, Ana Radović, Sam Shaaban, et al.
JMIR Formative Research (2022) Vol. 6, Iss. 6, pp. e35807-e35807
Open Access | Times Cited: 44
Digital Phenotyping for Monitoring Mental Disorders: Systematic Review
Pasquale Bufano, Marco Laurino, Sara Said, et al.
Journal of Medical Internet Research (2023) Vol. 25, pp. e46778-e46778
Open Access | Times Cited: 33
Depression detection on online social network with multivariate time series feature of user depressive symptoms
Yicheng Cai, Haizhou Wang, Huali Ye, et al.
Expert Systems with Applications (2023) Vol. 217, pp. 119538-119538
Closed Access | Times Cited: 24
Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning
Haishuai Wang, Paul Avillach
JMIR Medical Informatics (2021) Vol. 9, Iss. 4, pp. e24754-e24754
Open Access | Times Cited: 45
Capturing the College Experience
Subigya Nepal, Wenjun Liu, Arvind Pillai, et al.
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2024) Vol. 8, Iss. 1, pp. 1-37
Open Access | Times Cited: 6
Machine Learning Based Healthcare System for Investigating the Association Between Depression and Quality of Life
Masood Habib, Zhelong Wang, Sen Qiu, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 5, pp. 2008-2019
Closed Access | Times Cited: 27
A review of detection techniques for depression and bipolar disorder
Daniel Highland, Gang Zhou
Smart Health (2022) Vol. 24, pp. 100282-100282
Closed Access | Times Cited: 22
A Systematic Review of Location Data for Depression Prediction
Jaeeun Shin, Sung‐Man Bae
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 11, pp. 5984-5984
Open Access | Times Cited: 14
From Classification to Clinical Insights
Zachary Englhardt, Chengqian Ma, Margaret E. Morris, et al.
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2024) Vol. 8, Iss. 2, pp. 1-25
Open Access | Times Cited: 5
MoodCapture: Depression Detection using In-the-Wild Smartphone Images
Subigya Nepal, Arvind Pillai, Weichen Wang, et al.
(2024), pp. 1-18
Open Access | Times Cited: 4
Building an open-source community to enhance autonomic nervous system signal analysis: DBDP-autonomic
Jessilyn Dunn, Varun Mishra, Md Mobashir Hasan Shandhi, et al.
Frontiers in Digital Health (2025) Vol. 6
Open Access
Predictors of depression among Chinese college students: a machine learning approach
Lin Luo, Junfeng Yuan, Chenghan Wu, et al.
BMC Public Health (2025) Vol. 25, Iss. 1
Open Access
Predicting ESG Controversies in Banks Using Machine Learning Techniques
Anna Rita Dipierro, Fernando Jimenéz Barrionuevo, Pierluigi Toma
Corporate Social Responsibility and Environmental Management (2025)
Open Access
Enhancing Depression Detection Using EEG Signals Through Adaptive Feature Weighting in Extra Trees Classifier
Challa Madhavi Latha, M. Kezia Joseph
Smart innovation, systems and technologies (2025), pp. 583-592
Closed Access
Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study
Shayan Nejadshamsi, Vania Karami, Negar Ghourchian, et al.
JMIR Aging (2025) Vol. 8, pp. e67715-e67715
Open Access
Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic Review
Ali Kargarandehkordi, Shizhe Li, Kaiying Lin, et al.
Biosensors (2025) Vol. 15, Iss. 4, pp. 202-202
Open Access
Predictive Modeling of Mental Illness Onset Using Wearable Devices and Medical Examination Data: Machine Learning Approach
Tomoki Saito, Hikaru Suzuki, Akifumi Kishi
Frontiers in Digital Health (2022) Vol. 4
Open Access | Times Cited: 20
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