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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:

Multi-level Attention Network using Text, Audio and Video for Depression Prediction
Anupama Ray, Siddharth Krishna Kumar, Rutvik Reddy, et al.
(2019), pp. 81-88
Open Access | Times Cited: 97

Showing 1-25 of 97 citing articles:

Machine Learning in Mental Health
Anja Thieme, Danielle Belgrave, Gavin Doherty
ACM Transactions on Computer-Human Interaction (2020) Vol. 27, Iss. 5, pp. 1-53
Open Access | Times Cited: 290
Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment
Matthew Squires, Xiaohui Tao, Soman Elangovan, et al.
Brain Informatics (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 50
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: 23
CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation
Hao Sun, Hongyi Wang, Jiaqing Liu, et al.
Proceedings of the 30th ACM International Conference on Multimedia (2022), pp. 3722-3729
Open Access | Times Cited: 64
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: 62
Automatic depression recognition by intelligent speech signal processing: A systematic survey
Pingping Wu, Ruihao Wang, Han Lin, et al.
CAAI Transactions on Intelligence Technology (2022) Vol. 8, Iss. 3, pp. 701-711
Open Access | Times Cited: 52
Prediction of Depression Severity Based on the Prosodic and Semantic Features With Bidirectional LSTM and Time Distributed CNN
Kaining Mao, Wei Zhang, Deborah Baofeng Wang, et al.
IEEE Transactions on Affective Computing (2022) Vol. 14, Iss. 3, pp. 2251-2265
Open Access | Times Cited: 46
Cost-Sensitive Boosting Pruning Trees for Depression Detection on Twitter
Lei Tong, Zhihua Liu, Zheheng Jiang, et al.
IEEE Transactions on Affective Computing (2022) Vol. 14, Iss. 3, pp. 1898-1911
Open Access | Times Cited: 43
A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms
Ravi Prasad Thati, Abhishek Singh Dhadwal, Praveen Kumar, et al.
Multimedia Tools and Applications (2022) Vol. 82, Iss. 4, pp. 4787-4820
Open Access | Times Cited: 40
D-vlog: Multimodal Vlog Dataset for Depression Detection
Jeewoo Yoon, Chaewon Kang, Seungbae Kim, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 11, pp. 12226-12234
Open Access | Times Cited: 39
Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals
Huiting Fan, Xingnan Zhang, Yingying Xu, et al.
Information Fusion (2023) Vol. 104, pp. 102161-102161
Closed Access | Times Cited: 35
Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review
Piers Gooding, Timothy Kariotis
JMIR Mental Health (2021) Vol. 8, Iss. 6, pp. e24668-e24668
Open Access | Times Cited: 53
Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level
Hao Sun, Jiaqing Liu, Shurong Chai, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4764-4764
Open Access | Times Cited: 51
Depression Detection on Reddit With an Emotion-Based Attention Network: Algorithm Development and Validation
Lu Ren, Hongfei Lin, Bo Xu, et al.
JMIR Medical Informatics (2021) Vol. 9, Iss. 7, pp. e28754-e28754
Open Access | Times Cited: 47
Intelligent system for depression scale estimation with facial expressions and case study in industrial intelligence
Lang He, Chenguang Guo, Prayag Tiwari, et al.
International Journal of Intelligent Systems (2021) Vol. 37, Iss. 12, pp. 10140-10156
Open Access | Times Cited: 44
Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach
Ah Young Kim, Eun Hye Jang, Seung‐Hwan Lee, et al.
Journal of Medical Internet Research (2022) Vol. 25, pp. e34474-e34474
Open Access | Times Cited: 37
Deep Multi-Modal Network Based Automated Depression Severity Estimation
Md Azher Uddin, Joolekha Bibi Joolee, Kyung-Ah Sohn
IEEE Transactions on Affective Computing (2022) Vol. 14, Iss. 3, pp. 2153-2167
Closed Access | Times Cited: 35
Multi-modal Depression Estimation Based on Sub-attentional Fusion
Ping-Cheng Wei, Kunyu Peng, Alina Roitberg, et al.
Lecture notes in computer science (2023), pp. 623-639
Open Access | Times Cited: 20
A deep learning model for depression detection based on MFCC and CNN generated spectrogram features
Arnab Kumar Das, Ruchira Naskar
Biomedical Signal Processing and Control (2023) Vol. 90, pp. 105898-105898
Closed Access | Times Cited: 20
A comprehensive review of predictive analytics models for mental illness using machine learning algorithms
Md. Monirul Islam, Shahriar Hassan, Sharmin Akter, et al.
Healthcare Analytics (2024) Vol. 6, pp. 100350-100350
Open Access | Times Cited: 8
Acoustic and Facial Features From Clinical Interviews for Machine Learning–Based Psychiatric Diagnosis: Algorithm Development
Michael L. Birnbaum, Avner Abrami, Stephen Heisig, et al.
JMIR Mental Health (2022) Vol. 9, Iss. 1, pp. e24699-e24699
Open Access | Times Cited: 27
Spatial–Temporal Feature Network for Speech-Based Depression Recognition
Zhuojin Han, Yuanyuan Shang, Zhuhong Shao, et al.
IEEE Transactions on Cognitive and Developmental Systems (2023) Vol. 16, Iss. 1, pp. 308-318
Closed Access | Times Cited: 14
Semi-Structural Interview-Based Chinese Multimodal Depression Corpus Towards Automatic Preliminary Screening of Depressive Disorders
Bochao Zou, Jiali Han, Yingxue Wang, et al.
IEEE Transactions on Affective Computing (2022) Vol. 14, Iss. 4, pp. 2823-2838
Closed Access | Times Cited: 22
A novel automated depression detection technique using text transcript
Uma Yadav, Ashish K. Sharma
International Journal of Imaging Systems and Technology (2022) Vol. 33, Iss. 1, pp. 108-122
Closed Access | Times Cited: 21
TensorFormer: A Tensor-Based Multimodal Transformer for Multimodal Sentiment Analysis and Depression Detection
Hao Sun, Yen‐Wei Chen, Lanfen Lin
IEEE Transactions on Affective Computing (2022) Vol. 14, Iss. 4, pp. 2776-2786
Closed Access | Times Cited: 21
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