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:

Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals
Nicola Michielli, U. Rajendra Acharya, Filippo Molinari
Computers in Biology and Medicine (2019) Vol. 106, pp. 71-81
Closed Access | Times Cited: 339

Showing 1-25 of 339 citing articles:

SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
Sajad Mousavi, Fatemeh Afghah, U. Rajendra Acharya
PLoS ONE (2019) Vol. 14, Iss. 5, pp. e0216456-e0216456
Open Access | Times Cited: 399
An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG
Emadeldeen Eldele, Zhenghua Chen, Chengyu Liu, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 809-818
Open Access | Times Cited: 394
Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review
Mamunur Rashid, Norizam Sulaiman, Anwar P. P. Abdul Majeed, et al.
Frontiers in Neurorobotics (2020) Vol. 14
Open Access | Times Cited: 341
A new machine learning technique for an accurate diagnosis of coronary artery disease
Moloud Abdar, Wojciech Książek, U. Rajendra Acharya, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 179, pp. 104992-104992
Closed Access | Times Cited: 291
A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals
Özal Yıldırım, Ulaş Baran Baloğlu, U. Rajendra Acharya
International Journal of Environmental Research and Public Health (2019) Vol. 16, Iss. 4, pp. 599-599
Open Access | Times Cited: 221
A comparative analysis of signal processing and classification methods for different applications based on EEG signals
Ashima Khosla, Padmavati Khandnor, Trilok Chand
Journal of Applied Biomedicine (2020) Vol. 40, Iss. 2, pp. 649-690
Closed Access | Times Cited: 208
A Review of EEG Signal Features and Their Application in Driver Drowsiness Detection Systems
Igor Stančin, Mario Cifrek, Alan Jović
Sensors (2021) Vol. 21, Iss. 11, pp. 3786-3786
Open Access | Times Cited: 185
Artificial Intelligence and Internet of Things Enabled Disease Diagnosis Model for Smart Healthcare Systems
Romany F. Mansour, Adnen El Amraoui, Issam Nouaouri, et al.
IEEE Access (2021) Vol. 9, pp. 45137-45146
Open Access | Times Cited: 170
Scalp EEG classification using deep Bi-LSTM network for seizure detection
Xinmei Hu, Shasha Yuan, Fangzhou Xu, et al.
Computers in Biology and Medicine (2020) Vol. 124, pp. 103919-103919
Closed Access | Times Cited: 164
RETRACTED ARTICLE: EEG signal classification using LSTM and improved neural network algorithms
P. Nagabushanam, S. Thomas George, S. Radha
Soft Computing (2019) Vol. 24, Iss. 13, pp. 9981-10003
Closed Access | Times Cited: 151
EEG-based emotion recognition using hybrid CNN and LSTM classification
Bhuvaneshwari Chakravarthi, Sin-Chun Ng, M. R. Ezilarasan, et al.
Frontiers in Computational Neuroscience (2022) Vol. 16
Open Access | Times Cited: 79
State-of-the-Art on Brain-Computer Interface Technology
Jānis Pekša, Dmytro Mamchur
Sensors (2023) Vol. 23, Iss. 13, pp. 6001-6001
Open Access | Times Cited: 58
The applied principles of EEG analysis methods in neuroscience and clinical neurology
Hao Zhang, Qing-Qi Zhou, He Chen, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 49
A review of automated sleep stage scoring based on physiological signals for the new millennia
Oliver Faust, Hajar Razaghi, Ragab Barika, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 176, pp. 81-91
Open Access | Times Cited: 140
Classification of heart sound signals using a novel deep WaveNet model
Shu Lih Oh, Jahmunah Vicnesh, Chui Ping Ooi, et al.
Computer Methods and Programs in Biomedicine (2020) Vol. 196, pp. 105604-105604
Closed Access | Times Cited: 135
Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals
Özal Yıldırım, Muhammed Talo, Betül Ay, et al.
Computers in Biology and Medicine (2019) Vol. 113, pp. 103387-103387
Open Access | Times Cited: 133
Accurate Deep Learning-Based Sleep Staging in a Clinical Population with Suspected Obstructive Sleep Apnea
Henri Korkalainen, Timo Leppänen, Juhani Aakko, et al.
IEEE Journal of Biomedical and Health Informatics (2019), pp. 1-1
Open Access | Times Cited: 124
Convolution- and Attention-Based Neural Network for Automated Sleep Stage Classification
Tianqi Zhu, Wei Luo, Feng Yu
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 11, pp. 4152-4152
Open Access | Times Cited: 113
Automatic seizure detection based on imaged-EEG signals through fully convolutional networks
Catalina Gómez, Pablo Arbeláez, Miguel Navarrete, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 99
Automatic Sleep Stage Classification Using Temporal Convolutional Neural Network and New Data Augmentation Technique from Raw Single-Channel EEG
Ebrahim Khalili, Babak Mohammadzadeh Asl
Computer Methods and Programs in Biomedicine (2021) Vol. 204, pp. 106063-106063
Closed Access | Times Cited: 97
Automated detection of abnormal EEG signals using localized wavelet filter banks
Manish Sharma, Sohamkumar Patel, U. Rajendra Acharya
Pattern Recognition Letters (2020) Vol. 133, pp. 188-194
Closed Access | Times Cited: 94
A Multi-Scale Fusion Convolutional Neural Network Based on Attention Mechanism for the Visualization Analysis of EEG Signals Decoding
Donglin Li, Jiacan Xu, Jianhui Wang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 12, pp. 2615-2626
Closed Access | Times Cited: 94
Automated Detection of Sleep Stages Using Deep Learning Techniques: A Systematic Review of the Last Decade (2010–2020)
Hui Wen Loh, Chui Ping Ooi, Jahmunah Vicnesh, et al.
Applied Sciences (2020) Vol. 10, Iss. 24, pp. 8963-8963
Open Access | Times Cited: 92
Epileptic Seizure Detection Based on Stockwell Transform and Bidirectional Long Short-Term Memory
Minxing Geng, Weidong Zhou, Guoyang Liu, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 3, pp. 573-580
Closed Access | Times Cited: 80
DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model With Uncertainty Estimates
Luigi Fiorillo, Paolo Favaro, Francesca Faraci
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 2076-2085
Open Access | Times Cited: 80
Page 1 - Next Page

Scroll to top