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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:

Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone
Heejung Kim, SungHee Lee, SangEun Lee, et al.
JMIR mhealth and uhealth (2019) Vol. 7, Iss. 10, pp. e14149-e14149
Open Access | Times Cited: 109

Showing 1-25 of 109 citing articles:

Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study
Chul‐Hyun Cho, Taek Lee, Min-Gwan Kim, et al.
Journal of Medical Internet Research (2019) Vol. 21, Iss. 4, pp. e11029-e11029
Open Access | Times Cited: 151
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
Unravelling the complexities of depression with medical intelligence: exploring the interplay of genetics, hormones, and brain function
Md Belal Bin Heyat, Faijan Akhtar, Farwa Munir, et al.
Complex & Intelligent Systems (2024) Vol. 10, Iss. 4, pp. 5883-5915
Open Access | Times Cited: 19
Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study
Kennedy Opoku Asare, Yannik Terhorst, Julio Vega, et al.
JMIR mhealth and uhealth (2021) Vol. 9, Iss. 7, pp. e26540-e26540
Open Access | Times Cited: 99
Stress research during the COVID-19 pandemic and beyond
Lena Sophie Pfeifer, Katrin Heyers, Sebastian Ocklenburg, et al.
Neuroscience & Biobehavioral Reviews (2021) Vol. 131, pp. 581-596
Open Access | Times Cited: 56
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
Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence
Daniel Zarate, Vasileios Stavropoulos, M. Bethany Ball, et al.
BMC Psychiatry (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 51
How machine learning is used to study addiction in digital healthcare: A systematic review
Bijoy Chhetri, Lalit Mohan Goyal, Mamta Mittal
International Journal of Information Management Data Insights (2023) Vol. 3, Iss. 2, pp. 100175-100175
Open Access | Times Cited: 23
Intelligent Internet of Medical Things for Depression: Current Advancements, Challenges, and Trends
Md Belal Bin Heyat, Deepak Adhikari, Faijan Akhtar, et al.
International Journal of Intelligent Systems (2025) Vol. 2025, Iss. 1
Open Access | Times Cited: 1
Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives
Jayesh Kamath, Roberto León-Barriera, Neha Jain, et al.
World Journal of Psychiatry (2022) Vol. 12, Iss. 3, pp. 393-409
Open Access | Times Cited: 36
Late-life depression: Epidemiology, phenotype, pathogenesis and treatment before and during the COVID-19 pandemic
Yuanzhi Zhao, Xiangping Wu, Min Tang, et al.
Frontiers in Psychiatry (2023) Vol. 14
Open Access | Times Cited: 21
Wearable devices for anxiety & depression: A scoping review
Arfan Ahmed, Sarah Aziz, Mahmood Alzubaidi, et al.
Computer Methods and Programs in Biomedicine Update (2023) Vol. 3, pp. 100095-100095
Open Access | Times Cited: 20
Predicting the depression in university students using stacking ensemble techniques over oversampling method
Alfredo Daza Vergaray, Juan Carlos Herrera, Juana Bobadilla Cornelio, et al.
Informatics in Medicine Unlocked (2023) Vol. 41, pp. 101295-101295
Open Access | Times Cited: 19
mHealth Assessment and Intervention of Depression and Anxiety in Older Adults
Jason Grossman, Madelyn Frumkin, Thomas L. Rodebaugh, et al.
Harvard Review of Psychiatry (2020) Vol. 28, Iss. 3, pp. 203-214
Open Access | Times Cited: 49
Personalized Prediction of Behaviors and Experiences: An Idiographic Person–Situation Test
Emorie D Beck, Joshua J. Jackson
Psychological Science (2022) Vol. 33, Iss. 10, pp. 1767-1782
Open Access | Times Cited: 26
A Multirobot System in an Assisted Home Environment to Support the Elderly in Their Daily Lives
Ramón Barber, Francisco Ortiz, Santiago Garrido, et al.
Sensors (2022) Vol. 22, Iss. 20, pp. 7983-7983
Open Access | Times Cited: 23
Prediction models for depression risk among older adults: systematic review and critical appraisal
Jie Tan, Chenxinan Ma, Chonglin Zhu, et al.
Ageing Research Reviews (2022) Vol. 83, pp. 101803-101803
Closed Access | Times Cited: 23
Depressed Mood Prediction of Elderly People with a Wearable Band
Jinyoung Choi, Soo‐Min Lee, Seonyoung Kim, et al.
Sensors (2022) Vol. 22, Iss. 11, pp. 4174-4174
Open Access | Times Cited: 22
IMU-Based Monitoring for Assistive Diagnosis and Management of IoHT: A Review
Fan Bo, Mustafa Ozkan Yerebakan, Yanning Dai, et al.
Healthcare (2022) Vol. 10, Iss. 7, pp. 1210-1210
Open Access | Times Cited: 22
Digital phenotyping of geriatric depression using a community based digital mental health monitoring platform for socially vulnerable older adults and their community caregivers: A 6- week living lab single arm pilot study (Preprint)
Sunmi Song, YoungBin Seo, Seoyeon Hwang, et al.
JMIR mhealth and uhealth (2024) Vol. 12, pp. e55842-e55842
Open Access | Times Cited: 4
Application progress of Ecological Momentary Assessment technology in health management platform (Preprint)
Xiaoxiao Zhang, 觅之 吴, 佳楠 王, et al.
(2025)
Closed Access
App-Based Ecological Momentary Assessment of Problematic Smartphone Use During Examination Weeks in University Students: 6-Week Observational Study
Ji Seon Ahn, InJi Jeong, Sehwan Park, et al.
Journal of Medical Internet Research (2025) Vol. 27, pp. e69320-e69320
Open Access
Applying AI in the Context of the Association Between Device-Based Assessment of Physical Activity and Mental Health: Systematic Review
Simon Woll, Dennis Birkenmaier, Gergely Biri, et al.
JMIR mhealth and uhealth (2025) Vol. 13, pp. e59660-e59660
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
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