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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 Depression in Canada by Automatic Filling of Beck’s Depression Inventory Questionnaire
Ruba Skaik, Diana Inkpen
IEEE Access (2022) Vol. 10, pp. 102033-102047
Open Access | Times Cited: 11

Showing 11 citing articles:

On the incidence of depression symptoms on social media
Esteban A. Ríssola, Mario Ezra Aragón, David E. Losada, et al.
Journal of Computational Social Science (2025) Vol. 8, Iss. 2
Open Access
Artificial intelligence-based risk assessment tools for sexual, reproductive and mental health: a systematic review
Sadikul Islam, Rifat Shahriyar, Abhishek Agarwala, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
EEGDepressionNet: A Novel Self Attention-Based Gated DenseNet With Hybrid Heuristic Adopted Mental Depression Detection Model Using EEG Signals
Mustufa Haider Abidi, Khaja Moiduddin, Rashid Ayub, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 9, pp. 5168-5179
Closed Access | Times Cited: 2
Depression Level Detection Using AI
M. Venkatesan, Sheetal Pawar, Priyanka Thorat
(2024), pp. 1-5
Closed Access
IoT-Enabled Neural Network Analysis for Early Detection and Prediction of Mental Depression
Venkata Naga Lakshmi Likhitha Paruchuri, Abdul Hafeez Shaik, Dileep Kumar Murala, et al.
Lecture notes in networks and systems (2024), pp. 257-268
Closed Access
A Machine Learning based Depression Detection via Questionnaires and Video
Vijay P. Singh, Vineet Gupta, V. K. Tripathi, et al.
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2024), pp. 1-7
Closed Access
Dense Coordinate Channel Attention Network for Depression Level Estimation from Speech
Ziping Zhao, Shizhao Liu, Mingyue Niu, et al.
Lecture notes in computer science (2024), pp. 402-413
Closed Access
Depression diagnosis using Artificial Intelligence: a systematic review
Martín Di Felice, Ilan Trupkin, Ariel Deroche, et al.
F1000Research (2024) Vol. 13, pp. 1549-1549
Open Access
SOLWOE—A Novel Way to Diagnose Depression Among Teenagers
K. M. Anandkumar, VV Srinivas, J. Jayasurya, et al.
Lecture notes in networks and systems (2023), pp. 589-600
Closed Access
A Broad Survey on Detection of Depression in Societal Platforms using Machine Learning Model for the Public Health Care System
P Lakshmi Priya, R. Vijaya Prakash
(2023), pp. 1643-1649
Closed Access
Automatic Depression Detection Using Multi-Modal & Late-Fusion Based Architecture
Gyanendra Tiwary, Shivani Chauhan, K. K. Goyal
(2023), pp. 1-6
Closed Access
Prediction of Depression and Anxiety on University Students in Bangladesh Using Machine Learning
Afia Rahman, Anjuman Ara Ananna, Shekh Fahad, et al.
(2023)
Closed Access
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