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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:

A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images
Md. Zabirul Islam, Md. Milon Islam, Amanullah Asraf
Informatics in Medicine Unlocked (2020) Vol. 20, pp. 100412-100412
Open Access | Times Cited: 574

Showing 1-25 of 574 citing articles:

Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions
Iqbal H. Sarker
SN Computer Science (2021) Vol. 2, Iss. 6
Open Access | Times Cited: 1537
AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems
Iqbal H. Sarker
SN Computer Science (2022) Vol. 3, Iss. 2
Open Access | Times Cited: 654
Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images
Ramin Ranjbarzadeh, Abbas Bagherian Kasgari, Saeid Jafarzadeh Ghoushchi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 455
Breast Cancer Prediction: A Comparative Study Using Machine Learning Techniques
Md. Milon Islam, Md. Rezwanul Haque, Hasib Iqbal, et al.
SN Computer Science (2020) Vol. 1, Iss. 5
Open Access | Times Cited: 275
A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
Md. Milon Islam, Fakhri Karray, Reda Alhajj, et al.
IEEE Access (2021) Vol. 9, pp. 30551-30572
Open Access | Times Cited: 269
Collaborative Federated Learning for Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
Adnan Qayyum, Kashif Ahmad, Muhammad Ahtazaz Ahsan, et al.
IEEE Open Journal of the Computer Society (2022) Vol. 3, pp. 172-184
Open Access | Times Cited: 205
Applications of artificial intelligence in battling against covid-19: A literature review
Mohammad-H. Tayarani N.
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110338-110338
Open Access | Times Cited: 196
An Automated System to Limit COVID-19 Using Facial Mask Detection in Smart City Network
Mohammad Marufur Rahman, Md. Motaleb Hossen Manik, Md. Milon Islam, et al.
2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS) (2020), pp. 1-5
Open Access | Times Cited: 193
Short-term self consumption PV plant power production forecasts based on hybrid CNN-LSTM, ConvLSTM models
Ali Agga, Ahmed Abbou, Moussa Labbadi, et al.
Renewable Energy (2021) Vol. 177, pp. 101-112
Closed Access | Times Cited: 184
Deep learning for COVID-19 detection based on CT images
Wentao Zhao, Wei Jiang, Xinguo Qiu
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 167
Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review
Muzammil Khan, Muhammad Taqi Mehran, Zeeshan Haq, et al.
Expert Systems with Applications (2021) Vol. 185, pp. 115695-115695
Open Access | Times Cited: 167
Monkeypox Virus Detection Using Pre-trained Deep Learning-based Approaches
Chiranjibi Sitaula, Tej Bahadur Shahi
Journal of Medical Systems (2022) Vol. 46, Iss. 11
Open Access | Times Cited: 166
EMCNet: Automated COVID-19 diagnosis from X-ray images using convolutional neural network and ensemble of machine learning classifiers
Prottoy Saha, Muhammad Sheikh Sadi, Md. Milon Islam
Informatics in Medicine Unlocked (2020) Vol. 22, pp. 100505-100505
Open Access | Times Cited: 154
Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
Zaid Abdi Alkareem Alyasseri, Mohammed Azmi Al‐Betar, Iyad Abu Doush, et al.
Expert Systems (2021) Vol. 39, Iss. 3
Open Access | Times Cited: 141
Artificial Intelligence for COVID-19: A Systematic Review
Lian Wang, Yonggang Zhang, Dongguang Wang, et al.
Frontiers in Medicine (2021) Vol. 8
Open Access | Times Cited: 138
Graph Neural Network: A Comprehensive Review on Non-Euclidean Space
Nurul A. Asif, Yeahia Sarker, Ripon K. Chakrabortty, et al.
IEEE Access (2021) Vol. 9, pp. 60588-60606
Open Access | Times Cited: 134
A fuzzy-enhanced deep learning approach for early detection of Covid-19 pneumonia from portable chest X-ray images
Cosimo Ieracitano, Nadia Mammone, Mario Versaci, et al.
Neurocomputing (2022) Vol. 481, pp. 202-215
Open Access | Times Cited: 122
COVID-19 image classification using deep learning: Advances, challenges and opportunities
Priya Aggarwal, Narendra Kumar Mishra, Binish Fatimah, et al.
Computers in Biology and Medicine (2022) Vol. 144, pp. 105350-105350
Open Access | Times Cited: 119
Enhanced lung image segmentation using deep learning
Shilpa Gite, Abhinav Mishra, Ketan Kotecha
Neural Computing and Applications (2022) Vol. 35, Iss. 31, pp. 22839-22853
Open Access | Times Cited: 108
Hybrid quantum-classical convolutional neural network model for COVID-19 prediction using chest X-ray images
Essam H. Houssein, Zainab Abohashima, Mohamed Elhoseny, et al.
Journal of Computational Design and Engineering (2022) Vol. 9, Iss. 2, pp. 343-363
Open Access | Times Cited: 102
Detection of COVID-19 Based on Chest X-rays Using Deep Learning
Walaa Gouda, Maram Almurafeh, Mamoona Humayun, et al.
Healthcare (2022) Vol. 10, Iss. 2, pp. 343-343
Open Access | Times Cited: 89
Artificial intelligence for breast cancer analysis: Trends & directions
Shahid Munir Shah, Rizwan Ahmed Khan, Sheeraz Arif, et al.
Computers in Biology and Medicine (2022) Vol. 142, pp. 105221-105221
Open Access | Times Cited: 84
A review on the use of deep learning for medical images segmentation
Manar Aljabri, Manal Alghamdi
Neurocomputing (2022) Vol. 506, pp. 311-335
Closed Access | Times Cited: 74
Densely attention mechanism based network for COVID-19 detection in chest X-rays
Zahid Ullah, Muhammad Usman, Siddique Latif, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 46
A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
Asifullah Khan, Saddam Hussain Khan, Mahrukh Saif, et al.
Journal of Experimental & Theoretical Artificial Intelligence (2023) Vol. 36, Iss. 8, pp. 1779-1821
Open Access | Times Cited: 45
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