Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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

Showing 1-25 of 62 citing articles:

A Review of Key Technologies for Emotion Analysis Using Multimodal Information
Xianxun Zhu, Chaopeng Guo, Heyang Feng, et al.
Cognitive Computation (2024) Vol. 16, Iss. 4, pp. 1504-1530
Closed Access | Times Cited: 22
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
Integration of Artificial Intelligence and Wearable Internet of Things for Mental Health Detection
Wei Wang, Jian Chen, Yuzhu Hu, et al.
International Journal of Cognitive Computing in Engineering (2024) Vol. 5, pp. 307-315
Open Access | Times Cited: 11
Multimodal Sensing for Depression Risk Detection: Integrating Audio, Video, and Text Data
Zhenwei Zhang, Shengming Zhang, Dong Ni, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3714-3714
Open Access | Times Cited: 9
Depression Detection and Diagnosis Based on Electroencephalogram (EEG) Analysis: A Systematic Review
Kholoud Elnaggar, M. M. El-Gayar, Mohammed Elmogy
Diagnostics (2025) Vol. 15, Iss. 2, pp. 210-210
Open Access | Times Cited: 1
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
Diagnosis of mental disorders using machine learning: Literature review and bibliometric mapping from 2012 to 2023
Chandra Mani Sharma, Vijayaraghavan M. Chariar
Heliyon (2024) Vol. 10, Iss. 12, pp. e32548-e32548
Open Access | Times Cited: 5
FPT-Former: A Flexible Parallel Transformer of Recognizing Depression by Using Audiovisual Expert-Knowledge-Based Multimodal Measures
Yifu Li, Xueping Yang, Meng Zhao, et al.
International Journal of Intelligent Systems (2024) Vol. 2024, pp. 1-13
Open Access | Times Cited: 4
Enhancing multimodal depression diagnosis through representation learning and knowledge transfer
Shanliang Yang, Lichao Cui, Lei Wang, et al.
Heliyon (2024) Vol. 10, Iss. 4, pp. e25959-e25959
Open Access | Times Cited: 4
Human emotion recognition using Machine learning techniques based on the physiological signal
Akhilesh Kumar, Awadhesh Kumar
Biomedical Signal Processing and Control (2024) Vol. 100, pp. 107039-107039
Closed Access | Times Cited: 4
An Enhanced Cross‐Attention Based Multimodal Model for Depression Detection
Yifan Kou, Fangzhen Ge, Debao Chen, et al.
Computational Intelligence (2025) Vol. 41, Iss. 1
Closed Access
DepITCM: an audio-visual method for detecting depression
Lishan Zhang, Zhenhua Liu, Yumei Wan, et al.
Frontiers in Psychiatry (2025) Vol. 15
Open Access
Diagnosis of depression based on facial multimodal data
Na Jin, Rongzhen Ye, Peng Li
Frontiers in Psychiatry (2025) Vol. 16
Open Access
Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning
Zhong Ding, Jing Chen, Bao‐Liang Zhong, et al.
Journal of Affective Disorders (2025)
Closed Access
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
Application of multi-modal data fusion based on deep learning in diagnosis of depression
Pan Aizhen
Data & Metadata (2025) Vol. 4, pp. 863-863
Closed Access
Depression detection in read and spontaneous speech: A Multimodal approach for lesser-resourced languages
Klara Daly, Oluwafemi Olukoya
Biomedical Signal Processing and Control (2025) Vol. 108, pp. 107959-107959
Open Access
Multimodal interior comfort evaluation via odor and vision information
Yujiao Ji, Han Wang, Lei Jin, et al.
Measurement (2025), pp. 117773-117773
Closed Access
Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module
Muath Alsuhaibani, Hiroko H. Dodge, Mohammad H. Mahoor
Expert Systems with Applications (2024) Vol. 252, pp. 124185-124185
Open Access | Times Cited: 3
DDoS detection in electric vehicle charging stations: A deep learning perspective via CICEV2023 dataset
Yagiz Alp Anli, Zeki Çıplak, Murat Sakaliuzun, et al.
Internet of Things (2024) Vol. 28, pp. 101343-101343
Closed Access | Times Cited: 3
Text-guided multimodal depression detection via cross-modal feature reconstruction and decomposition
Z Chen, Dandan Wang, Liangliang Lou, et al.
Information Fusion (2024), pp. 102861-102861
Closed Access | Times Cited: 3
A novel multimodal depression diagnosis approach utilizing a new hybrid fusion method
Xiufeng Zhang, Bingyi Li, Guobin Qi
Biomedical Signal Processing and Control (2024) Vol. 96, pp. 106552-106552
Closed Access | Times Cited: 2
Development of multimodal sentiment recognition and understanding
Jianhua Tao, Cunhang Fan, Zheng Lian, et al.
Journal of Image and Graphics (2024) Vol. 29, Iss. 6, pp. 1607-1627
Closed Access | Times Cited: 2
Automatic depression prediction via cross-modal attention-based multi-modal fusion in social networks
Lidong Wang, Yin Zhang, Bin Zhou, et al.
Computers & Electrical Engineering (2024) Vol. 118, pp. 109413-109413
Closed Access | Times Cited: 2
A New Regression Model for Depression Severity Prediction Based on Correlation among Audio Features Using a Graph Convolutional Neural Network
Momoko Ishimaru, Yoshifumi Okada, Ryunosuke Uchiyama, et al.
Diagnostics (2023) Vol. 13, Iss. 4, pp. 727-727
Open Access | Times Cited: 6
Page 1 - Next Page

Scroll to top