- Decision support system for major depression detection using spectrogram and convolution neural network with <scp>EEG</scp> signals
Hui Wen Loh, Chui Ping Ooi, Emrah Aydemir, Türker Tuncer, Şengül Doğan, U. Rajendra Acharya · 2021 · Expert Systems
Cites dataset 100 citations
- Automated diagnosis of depression from EEG signals using traditional and deep learning approaches: A comparative analysis
Ashima Khosla, Padmavati Khandnor, Trilok Chand · 2021 · Journal of Applied Biomedicine
Cites dataset 82 citations
- Deep-Asymmetry: Asymmetry Matrix Image for Deep Learning Method in Pre-Screening Depression
Min Kang, Hyunjin Kwon, Jinhyeok Park, Seokhwan Kang, Youngho Lee · 2020 · Sensors
Cites dataset 71 citations
- Automated major depressive disorder detection using melamine pattern with EEG signals
Emrah Aydemir, Türker Tuncer, Şengül Doğan, Raj Gururajan, U. Rajendra Acharya · 2021 · Applied Intelligence
Cites dataset 59 citations
- Benchmarks for machine learning in depression discrimination using electroencephalography signals
Ayan Seal, Rishabh Bajpai, Mohan Karnati, Jagriti Agnihotri, Anis Yazidi, Enrique Herrera‐Viedma, Ondřej Krejcar · 2022 · Applied Intelligence
Cites dataset 44 citations
- DiffMDD: A Diffusion-Based Deep Learning Framework for MDD Diagnosis Using EEG
Yilin Wang, Sha Zhao, Haiteng Jiang, Shijian Li, Benyan Luo, Tao Li, Gang Pan · 2024 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
Cites dataset 42 citations
- Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorder
Friedrich Philipp Carrle, Yasmin Hollenbenders, Alexandra Reichenbach · 2023 · Frontiers in Neuroscience
Cites dataset 32 citations
- MAST-GCN: Multi-Scale Adaptive Spatial-Temporal Graph Convolutional Network for EEG-Based Depression Recognition
Haifeng Lu, Zhiyang You, Yi Guo, Xiping Hu · 2024 · IEEE Transactions on Affective Computing
Cites dataset 27 citations
- DCTNet: hybrid deep neural network-based EEG signal for detecting depression
Yu Chen, Sheng Wang, Jifeng Guo · 2023 · Multimedia Tools and Applications
Cites dataset 23 citations
- Multi-Granularity Graph Convolution Network for Major Depressive Disorder Recognition
Xiaofang Sun, Yonghui Xu, Yibowen Zhao, Xiangwei Zheng, Yongqing Zheng, Lizhen Cui · 2023 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
Cites dataset 21 citations
- M-MDD: A multi-task deep learning framework for major depressive disorder diagnosis using EEG
Yilin Wang, Sha Zhao, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan · 2025 · Neurocomputing
Cites dataset 15 citations
- Graph convolution network-based eeg signal analysis: a review
Hui Xiong, Yan Yan, Yimei Chen, Jinzhen Liu · 2025 · Medical & Biological Engineering & Computing
Cites dataset 10 citations
- Delaunay Triangulated Simplicial Complex Generation for EEG Signal Classification
Srikireddy Dhanunjay Reddy, Tharun Kumar Reddy · 2024 · IEEE Sensors Letters
Cites dataset 10 citations
- Neurophysiological biomarkers for depression classification: Utilizing microstate k-mers and a bag-of-words model
Dongdong Zhou, Xinyu Peng, Lin Zhao, Lingli Ma, Jinhui Hu, Zhenghao Jiang, Xiaoqing He, Wo Wang, R.-W. Chen, Li Kuang · 2023 · Journal of Psychiatric Research
Cites dataset 8 citations
- Decentralized EEG-based detection of major depressive disorder via transformer architectures and split learning
Muhammad Umair, Jawad Ahmad, Nada Alasbali, Oumaima Saidani, Muhammad Fainan Hanif, Aizaz Ahmad Khattak, Muhammad Shahbaz Khan · 2025 · Frontiers in Computational Neuroscience
Cites dataset 8 citations
- EEG-based depression classification using harmonized datasets
Vladimir Savinov, Viktor Sapunov, Natalia Shusharina, Stepan Botman, Gleb Kamyshov, A. M. Tynterova · 2021 · n/a
Cites dataset 8 citations
- Optimizing Depression Classification Using Combined Datasets and Hyperparameter Tuning with Optuna
Ștefana Duță, Alina Sultana · 2025 · Sensors
Cites dataset 7 citations
- EEG foundation models: a critical review of current progress and future directions
Gayal Kuruppu, Neeraj Wagh, Václav Křemen, Yogatheesan Varatharajah · 2026 · Journal of Neural Engineering
Cites dataset 5 citations
- A Hybrid Neural Network Approach Based on RNN and CNN for the Detection of Major Depressive Disorder
Konapala Srilakshmi Anjana Priya, Hema Kumar Goru, Kunapareddy Kavya Priya, Bevara Dinesh Sai Manikanta · 2024 · n/a
Cites dataset 3 citations
- LightFFNet: MDD Prediction on EEG Quantitative Biomarkers
Urvashi Prakash Shukla, Shreeya Garg · 2022 · 2022 International Conference on Engineering and Emerging Technologies (ICEET)
Cites dataset 1 citations
- Depression Diagnosis Using Optimization of Nonlinear EEG Features Based on Parametric Learning Tactics
Ali Asadi Zeidabadi, Melika Changizi, Mahdi Zolfagharzadeh Kermani, Sara Bargi Barkouk · 2024 · n/a
Cites dataset 1 citations
- Brain Functional Residual Temporal Convolution Network for Major Depressive Disorder Recognition
Xiaofang Sun, Yonghui Xu, Xiangwei Zheng, Wei Guo, Wei He, Yali Jiang, Yongqing Zheng, Lizhen Cui · 2023 · n/a
Cites dataset 1 citations
- A Hybrid Quantum-Classical Multiscale LSTM Framework for Subject-Level EEG-Based Depression Detection
Sathiya E, Chunzhuo Wang, T.D. Rao, T. Sunil Kumar · 2026 · medRxiv
Cites dataset
- Methodology of collection, recording and markup of biophysical multimodal data in the study of human psychoemotional states
Natalia Shusharina · 2024 · Izvestiya of Saratov University Physics
Cites dataset
- infoEEG-TM: A Non-Pretrained EEG Representation Learning Framework Basedon Information Theory
Jiang Wu, Huan Gao, Shangyang Li, Tao Lu · 2025 · SSRN Electronic Journal
Cites dataset
- A machine learning approach based on EEG signals for detection of depression
Prajakta Rohan Naregalkar, Arundhati A. Shinde, Mangal Patil · 2025 · Engineering Research Express
Cites dataset
- Advancing Clinical Trust in Deep Learning EEG Depression Detection Model: A Systematic Analysis of Demographic Influences, Task Dynamics, and AI Explainability
Sumathi Balakrishnan, B.S.M. Ronald, Gregorius Hans Andreanto, WeiWei Goh, M. Nagentrau · 2025 · Algorithms for intelligent systems
Cites dataset
- Efficiency of convolutional neural networks of different architecture for the task of depression diagnosis from EEG data
Natalia Shusharina · 2024 · Izvestiya VUZ Applied Nonlinear Dynamics
Cites dataset
- Reproducibility of electroencephalography biomarkers for diagnosis of major depressive disorder
Yasmin Hollenbenders, Christoph Maier, Alexandra Reichenbach, Christoph Maier, Alexandra Reichenbach · 2024 · medRxiv
Cites dataset
- An optimized EEG-based intrinsic brain network for depression detection using differential graph centrality
Nausheen Ansari, Yusuf Uzzaman Khan, Omar Farooq · 2025 · Biomedical Physics & Engineering Express
Cites dataset
- Handcrafted Versus Deep Transfer Learning Features for EEG-Based Detection of Major Depressive Disorder
Harsh Bhasin, Nishtha Nagar, Tanish · 2026 · Lecture notes in networks and systems
Cites dataset
- NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning
Guoan Wang, Shihao Yang, Jun-En Ding, Hao Zhu, Feng Liu · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
Cites dataset
No citations of that kind for this dataset.