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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:

Improving depression prediction using a novel feature selection algorithm coupled with context-aware analysis
Zhijun Dai, Heng Zhou, Qingfang Ba, et al.
Journal of Affective Disorders (2021) Vol. 295, pp. 1040-1048
Closed Access | Times Cited: 21

Showing 21 citing articles:

A multimodal fusion model with multi-level attention mechanism for depression detection
Ming Fang, Siyu Peng, Yujia Liang, et al.
Biomedical Signal Processing and Control (2022) Vol. 82, pp. 104561-104561
Closed Access | Times Cited: 61
Automatic depression severity assessment with deep learning using parameter-efficient tuning
Clinton K. Lau, Xiaodan Zhu, Wai-Yip Chan
Frontiers in Psychiatry (2023) Vol. 14
Open Access | Times Cited: 17
Depression recognition using a proposed speech chain model fusing speech production and perception features
Ming‐Hao Du, Shuang Liu, Tao Wang, et al.
Journal of Affective Disorders (2022) Vol. 323, pp. 299-308
Open Access | Times Cited: 22
A Review of Machine Learning-Based Assessment of Depression
Zhao Wang, Ziyi Cai, Shuya Dong, et al.
Communications in computer and information science (2025), pp. 266-290
Closed Access
A Hybrid Feature Selection and Ensemble Approach to Identify Depressed Users in Online Social Media
Jingfang Liu, Mengshi Shi
Frontiers in Psychology (2022) Vol. 12
Open Access | Times Cited: 20
A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
Arturo Montejo‐Ráez, M. Dolores Molina-González, Salud María Jiménez-Zafra, et al.
Computer Science Review (2024) Vol. 53, pp. 100654-100654
Open Access | Times Cited: 4
A Survey of Current Progress in Depression Detection Using Deep Learning and Machine Learning
Meena Kumari, Gurpreet Singh, Sagar Dhanraj Pande
Deleted Journal (2025)
Closed Access
Towards automatic text-based estimation of depression through symptom prediction
Kirill Milintsevich, Kairit Sirts, Gaël Dias
Brain Informatics (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 10
Three-Stream Convolutional Neural Network for Depression Detection With Ocular Imaging
Minqiang Yang, Ziru Weng, Yuhong Zhang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 4921-4930
Open Access | Times Cited: 10
D-ResNet-PVKELM: deep neural network and paragraph vector based kernel extreme machine learning model for multimodal depression analysis
Swasthika Jain T J, I. Jeena Jacob, Ajay Kumar Mandava
Multimedia Tools and Applications (2023) Vol. 82, Iss. 17, pp. 25973-26004
Closed Access | Times Cited: 8
Improving Depression Prediction Accuracy Using Fisher Score-Based Feature Selection and Dynamic Ensemble Selection Approach Based on Acoustic Features of Speech
Janardhan Naulegari, Nandhini Kumaresh
Traitement du signal (2022) Vol. 39, Iss. 1, pp. 87-107
Open Access | Times Cited: 13
The use of machine learning and deep learning models in detecting depression on social media: A systematic literature review
Wadzani Aduwamai Gadzama, Danlami Gabi, Musa Sule Argungu, et al.
Personalized Medicine in Psychiatry (2024) Vol. 45-46, pp. 100125-100125
Closed Access | Times Cited: 1
Construction method of college students' depression knowledge map based on education big data
Shanwen Zhang, Chang-Qing Yu, Xuqi Wang, et al.
Adult and Higher Education (2023) Vol. 5, Iss. 4
Open Access | Times Cited: 2
A Multimodal Fusion Model with Multi-Level Attention Mechanism for Depression Detection
Ming Fang, Siyu Peng, Yujia Liang, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 4
Towards Automatic Text-Based Estimation of Depression through Symptom Prediction
Kirill Milintsevich, Kairit Sirts, Gaël Dias
Research Square (Research Square) (2022)
Open Access | Times Cited: 3
Multi-view graph-based interview representation to improve depression level estimation
Navneet Agarwal, Gaël Dias, Sonia Dollfus
Brain Informatics (2024) Vol. 11, Iss. 1
Open Access
HEAR set: A ligHtwEight acoustic paRameters set to assess mental health from voice analysis
Laura Verde, Fiammetta Marulli, Roberta De Fazio, et al.
Computers in Biology and Medicine (2024) Vol. 182, pp. 109021-109021
Open Access
Textual-dominated Multimodal Depression Detection
Kuan Huang, Heli Lu, Jing Li
2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) (2024), pp. 1-6
Closed Access
iPReditor-CMG: Improving a predictive RNA editor for crop mitochondrial genomes using genomic sequence features and an optimal support vector machine
Sidong Qin, Yanjun Fan, Shengnan Hu, et al.
Phytochemistry (2022) Vol. 200, pp. 113222-113222
Closed Access | Times Cited: 1
A Multimodal Fusion Model with Multi-Level Attention Mechanism for Depression Detection
Ming Fang, Siyu Peng, Yujia Liang, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 1
iPReditor-CMG: Improving Predictive RNA Editor for Crop Mitochondrial Genomes Using Genomic Sequence Features and Optimal Support Vector Machine
Sidong Qin, Yanjun Fan, Shengnan Hu, et al.
(2021)
Open Access | Times Cited: 1
Bi-stage QWOA-Based Efficient Feature Selection for Enhanced Depression Detection Based on Facial Cues
Swati Rathi, Baljeet Kaur, R. K. Agrawal
Lecture notes in networks and systems (2023), pp. 248-264
Closed Access
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