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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:

AUTOMATED DIAGNOSIS OF NORMAL AND ALCOHOLIC EEG SIGNALS
U. Rajendra Acharya, S. Vinitha Sree, Subhagata Chattopadhyay, et al.
International Journal of Neural Systems (2012) Vol. 22, Iss. 03, pp. 1250011-1250011
Closed Access | Times Cited: 168

Showing 1-25 of 168 citing articles:

Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals
Rajeev Sharma, Ram Bilas Pachori, U. Rajendra Acharya
Entropy (2015) Vol. 17, Iss. 2, pp. 669-691
Open Access | Times Cited: 297
Automated detection of schizophrenia using nonlinear signal processing methods
Jahmunah Vicnesh, Shu Lih Oh, V. Rajinikanth, et al.
Artificial Intelligence in Medicine (2019) Vol. 100, pp. 101698-101698
Closed Access | Times Cited: 199
Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis
Siuly Siuly, Yanchun Zhang
Data Science and Engineering (2016) Vol. 1, Iss. 2, pp. 54-64
Open Access | Times Cited: 182
Stress Detection Using Wearable Physiological and Sociometric Sensors
Óscar Martínez Mozos, Virginia Săndulescu, Sally Andrews, et al.
International Journal of Neural Systems (2016) Vol. 27, Iss. 02, pp. 1650041-1650041
Open Access | Times Cited: 175
An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism
Shivnarayan Patidar, Ram Bilas Pachori, Abhay Upadhyay, et al.
Applied Soft Computing (2016) Vol. 50, pp. 71-78
Closed Access | Times Cited: 119
Diagnosis and prognosis of mental disorders by means of EEG and deep learning: a systematic mapping study
Manuel J. Rivera, Miguel A. Teruel, Alejandro Maté, et al.
Artificial Intelligence Review (2021) Vol. 55, Iss. 2, pp. 1209-1251
Closed Access | Times Cited: 64
Classification of alcoholic EEG signals using wavelet scattering transform-based features
Abdul Baseer Buriro, Bilal Ahmed, Gulsher Baloch, et al.
Computers in Biology and Medicine (2021) Vol. 139, pp. 104969-104969
Closed Access | Times Cited: 60
Alcoholic EEG signals recognition based on phase space dynamic and geometrical features
Muhammad Tariq Sadiq, Hesam Akbari, Siuly Siuly, et al.
Chaos Solitons & Fractals (2022) Vol. 158, pp. 112036-112036
Closed Access | Times Cited: 57
A novel method for diagnosing Alzheimer's disease using deep pyramid CNN based on EEG signals
Wei Xia, Ran Zhang, Xiao Zhang, et al.
Heliyon (2023) Vol. 9, Iss. 4, pp. e14858-e14858
Open Access | Times Cited: 27
How machine learning is used to study addiction in digital healthcare: A systematic review
Bijoy Chhetri, Lalit Mohan Goyal, Mamta Mittal
International Journal of Information Management Data Insights (2023) Vol. 3, Iss. 2, pp. 100175-100175
Open Access | Times Cited: 21
Real-Time EEG-Based Detection of Fatigue Driving Danger for Accident Prediction
Hong Wang, Chi Zhang, Tianwei Shi, et al.
International Journal of Neural Systems (2014) Vol. 25, Iss. 02, pp. 1550002-1550002
Closed Access | Times Cited: 92
A Wavelet-Statistical Features Approach for Nonconvulsive Seizure Detection
Priyanka Sharma, Yusuf Uzzaman Khan, Omar Farooq, et al.
Clinical EEG and Neuroscience (2014) Vol. 45, Iss. 4, pp. 274-284
Closed Access | Times Cited: 91
Classification of Obsessive Compulsive Disorder by EEG Complexity and Hemispheric Dependency Measurements
Serap Aydın, Nafiz Arıca, Emrah Ergül, et al.
International Journal of Neural Systems (2015) Vol. 25, Iss. 03, pp. 1550010-1550010
Closed Access | Times Cited: 77
Dual-Tree Complex Wavelet Transform-Based Features for Automated Alcoholism Identification
Manish Sharma, Pragya Sharma, Ram Bilas Pachori, et al.
International Journal of Fuzzy Systems (2018) Vol. 20, Iss. 4, pp. 1297-1308
Closed Access | Times Cited: 73
Empirical wavelet transform based automated alcoholism detecting using EEG signal features
Arti Anuragi, Dilip Singh Sisodia
Biomedical Signal Processing and Control (2019) Vol. 57, pp. 101777-101777
Closed Access | Times Cited: 71
An EEG-based machine learning method to screen alcohol use disorder
Wajid Mumtaz, Pham Lam Vuong, Likun Xia, et al.
Cognitive Neurodynamics (2016) Vol. 11, Iss. 2, pp. 161-171
Open Access | Times Cited: 69
Alcohol use disorder detection using EEG Signal features and flexible analytical wavelet transform
Arti Anuragi, Dilip Singh Sisodia
Biomedical Signal Processing and Control (2018) Vol. 52, pp. 384-393
Closed Access | Times Cited: 68
A novel three-band orthogonal wavelet filter bank method for an automated identification of alcoholic EEG signals
Manish Sharma, Dipankar Deb, U. Rajendra Acharya
Applied Intelligence (2017)
Closed Access | Times Cited: 63
Classification of Alcoholic EEG Signals Using a Deep Learning Method
Leila Farsi, Siuly Siuly, Enamul Kabir, et al.
IEEE Sensors Journal (2020) Vol. 21, Iss. 3, pp. 3552-3560
Closed Access | Times Cited: 63
Classification of EEG signals to detect alcoholism using machine learning techniques
Jardel das C. Rodrigues, Pedro P. Rebouças Filho, Eugênio Peixoto, et al.
Pattern Recognition Letters (2019) Vol. 125, pp. 140-149
Closed Access | Times Cited: 62
A Framework for Schizophrenia EEG Signal Classification With Nature Inspired Optimization Algorithms
Sunil Kumar Prabhakar, Harikumar Rajaguru, Seong‐Whan Lee
IEEE Access (2020) Vol. 8, pp. 39875-39897
Open Access | Times Cited: 61
Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study
Sivan Kinreich, Jacquelyn L. Meyers, Adi Maron‐Katz, et al.
Molecular Psychiatry (2019) Vol. 26, Iss. 4, pp. 1133-1141
Open Access | Times Cited: 54
Machine learning with neuroimaging biomarkers: Application in the diagnosis and prediction of drug addiction
Longtao Yang, Yanyao Du, Wenhan Yang, et al.
Addiction Biology (2023) Vol. 28, Iss. 2
Closed Access | Times Cited: 20
Prediction of O-6-methylguanine-DNA methyltransferase and overall survival of the patients suffering from glioblastoma using MRI-based hybrid radiomics signatures in machine and deep learning framework
Sanjay Saxena, Aaditya Agrawal, Pankaj Kumar, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 18, pp. 13647-13663
Closed Access | Times Cited: 16
EPILEPTIC EEG CLASSIFICATION BASED ON KERNEL SPARSE REPRESENTATION
Qi Yuan, Weidong Zhou, Shasha Yuan, et al.
International Journal of Neural Systems (2014) Vol. 24, Iss. 04, pp. 1450015-1450015
Closed Access | Times Cited: 64
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