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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:

EPSPatNet86: eight-pointed star pattern learning network for detection ADHD disorder using EEG signals
Dahiru Tanko, Prabal Datta Barua, Şengül Doğan, et al.
Physiological Measurement (2022) Vol. 43, Iss. 3, pp. 035002-035002
Closed Access | Times Cited: 15

Showing 15 citing articles:

Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Smith K. Khare, Sonja March, Prabal Datta Barua, et al.
Information Fusion (2023) Vol. 99, pp. 101898-101898
Open Access | Times Cited: 72
An explainable and interpretable model for attention deficit hyperactivity disorder in children using EEG signals
Smith K. Khare, U. Rajendra Acharya
Computers in Biology and Medicine (2023) Vol. 155, pp. 106676-106676
Open Access | Times Cited: 54
Detection of ADHD cases using CNN and classical classifiers of raw EEG
Behrad TaghiBeyglou, Ashkan Shahbazi, Fatemeh Bagheri, et al.
Computer Methods and Programs in Biomedicine Update (2022) Vol. 2, pp. 100080-100080
Open Access | Times Cited: 41
QLBP: Dynamic patterns-based feature extraction functions for automatic detection of mental health and cognitive conditions using EEG signals
Gülay TAŞCI, Mehmet Veysel Gün, Tuğçe Keleş, et al.
Chaos Solitons & Fractals (2023) Vol. 172, pp. 113472-113472
Closed Access | Times Cited: 17
A novel approach to identify the brain regions that best classify ADHD by means of EEG and deep learning
Javier Sanchís, Sandra García-Ponsoda, Miguel A. Teruel, et al.
Heliyon (2024) Vol. 10, Iss. 4, pp. e26028-e26028
Open Access | Times Cited: 6
Detection of ADHD from EEG signals using new hybrid decomposition and deep learning techniques
Mustafa Yasin Esas, Fatma Lati̇foğlu
Journal of Neural Engineering (2023) Vol. 20, Iss. 3, pp. 036028-036028
Open Access | Times Cited: 13
Attention deficit hyperactivity disorder detection in children using multivariate empirical EEG decomposition approaches: A comprehensive analytical study
Yogesh Sharma, Bikesh Kumar Singh
Expert Systems with Applications (2022) Vol. 213, pp. 119219-119219
Closed Access | Times Cited: 14
Siamese based deep neural network for ADHD detection using EEG signal
Behnam Latifi, Ali Amini, Ali Motie Nasrabadi
Computers in Biology and Medicine (2024) Vol. 182, pp. 109092-109092
Closed Access | Times Cited: 2
Improved ADHD Diagnosis Using EEG Connectivity and Deep Learning through Combining Pearson Correlation Coefficient and Phase-Locking Value
Elham Ahmadi Moghadam, Farhad Abedinzadeh Torghabeh, Seyyed Abed Hosseini, et al.
Neuroinformatics (2024) Vol. 22, Iss. 4, pp. 521-537
Closed Access | Times Cited: 2
Multiple tangent space projection for motor imagery EEG classification
Sara Omari, Adil Omari, Mohamed Abderrahim
Applied Intelligence (2023) Vol. 53, Iss. 18, pp. 21192-21200
Open Access | Times Cited: 6
ADHD classification combining biomarker detection with attention auto-encoding neural network
Ying Chen, Yuan Gao, Aimin Jiang, et al.
Biomedical Signal Processing and Control (2023) Vol. 84, pp. 104733-104733
Closed Access | Times Cited: 5
An accurate automated speaker counting architecture based on James Webb Pattern
Prabal Datta Barua, Arif Metehan Yıldız, Nida Canpolat, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 119, pp. 105821-105821
Closed Access | Times Cited: 4
Grid-tuned ensemble models for 2D spectrogram-based autism classification
Muhammad Zakir Ullah, Dongchuan Yu
Biomedical Signal Processing and Control (2024) Vol. 93, pp. 106151-106151
Closed Access | Times Cited: 1
RESNET34 with Synchrosqueezing Transform for ADHD Disorder Detection Using EEG Signals
N. Arunkumar, B. Nagaraj, M. Ruth Keziah
Fluctuation and Noise Letters (2024) Vol. 23, Iss. 05
Closed Access
Exploring role of prefrontal cortex region of brain in children having ADHD with machine learning: Implications and insights
Manjusha Deshmukh, Mahi Khemchandani, Paramjit Mahesh Thakur
Applied Neuropsychology Child (2024), pp. 1-13
Closed Access
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