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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:

Machine learning-based prediction of COVID-19 diagnosis based on symptoms
Yazeed Zoabi, Shira Deri-Rozov, Noam Shomron
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 468

Showing 1-25 of 468 citing articles:

Machine learning-based approach: global trends, research directions, and regulatory standpoints
Raffaele Pugliese, Stefano Regondi, Riccardo Marini
Data Science and Management (2021) Vol. 4, pp. 19-29
Open Access | Times Cited: 223
Machine learning and deep learning approach for medical image analysis: diagnosis to detection
Meghavi Rana, Megha Bhushan
Multimedia Tools and Applications (2022) Vol. 82, Iss. 17, pp. 26731-26769
Open Access | Times Cited: 151
From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers
Hari Viswanathan, Jonathan Ajo‐Franklin, Jens Birkhölzer, et al.
Reviews of Geophysics (2022) Vol. 60, Iss. 1
Open Access | Times Cited: 145
Trends in Using IoT with Machine Learning in Health Prediction System
Amani Aldahiri, Bashair Ali Alrashed, Walayat Hussain
Forecasting (2021) Vol. 3, Iss. 1, pp. 181-206
Open Access | Times Cited: 132
Review of Current COVID-19 Diagnostics and Opportunities for Further Development
Yan Mardian, Herman Kosasih, Muhammad Karyana, et al.
Frontiers in Medicine (2021) Vol. 8
Open Access | Times Cited: 126
Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives
Shigao Huang, Jie Yang, Simon Fong, et al.
International Journal of Biological Sciences (2021) Vol. 17, Iss. 6, pp. 1581-1587
Open Access | Times Cited: 118
Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence
Bangfeng Wang, Yiwei Li, Mengfan Zhou, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 107
Telehealth and Artificial Intelligence Insights into Healthcare during the COVID-19 Pandemic
Dina M. El‐Sherif, Mohamed Abouzid, Mohamed Tarek Elzarif, et al.
Healthcare (2022) Vol. 10, Iss. 2, pp. 385-385
Open Access | Times Cited: 95
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review
Felipe Giuste, Wenqi Shi, Yuanda Zhu, et al.
IEEE Reviews in Biomedical Engineering (2022) Vol. 16, pp. 5-21
Open Access | Times Cited: 84
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder
IEEE Transactions on Artificial Intelligence (2023) Vol. 5, Iss. 4, pp. 1429-1442
Open Access | Times Cited: 81
Automatic COVID-19 prediction using explainable machine learning techniques
Sanzida Solayman, Sk. Azmiara Aumi, Chand Sultana Mery, et al.
International Journal of Cognitive Computing in Engineering (2023) Vol. 4, pp. 36-46
Open Access | Times Cited: 57
Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment
Md. Mahadi Hasan, Muhammad Usama Islam, Muhammad Jafar Sadeq, et al.
Sensors (2023) Vol. 23, Iss. 1, pp. 527-527
Open Access | Times Cited: 46
End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study
Harry Coppock, Alex Gaskell, Panagiotis Tzirakis, et al.
BMJ Innovations (2021) Vol. 7, Iss. 2, pp. 356-362
Open Access | Times Cited: 96
Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases
Ania Syrowatka, Masha Kuznetsova, Ava Alsubai, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 89
Optimization and fine-tuning of DenseNet model for classification of COVID-19 cases in medical imaging
Tavishee Chauhan, Hemant Palivela, Sarveshmani Tiwari
International Journal of Information Management Data Insights (2021) Vol. 1, Iss. 2, pp. 100020-100020
Open Access | Times Cited: 71
COVID-19 detection from CT scans using a two-stage framework
Arpan Basu, Khalid Hassan Sheikh, Erik Cuevas, et al.
Expert Systems with Applications (2022) Vol. 193, pp. 116377-116377
Open Access | Times Cited: 67
Data-Driven Machine-Learning Methods for Diabetes Risk Prediction
Ηλίας Δρίτσας, Μαρία Τρίγκα
Sensors (2022) Vol. 22, Iss. 14, pp. 5304-5304
Open Access | Times Cited: 66
A Multifaceted benchmarking of synthetic electronic health record generation models
Chao Yan, Yao Yan, Zhiyu Wan, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 60
A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis
Mohammad Moradi, Reza Golmohammadi, Ali Najafi, et al.
Informatics in Medicine Unlocked (2022) Vol. 28, pp. 100862-100862
Open Access | Times Cited: 54
Initial Stage COVID-19 Detection System Based on Patients’ Symptoms and Chest X-Ray Images
Mohammad Attaullah, Mushtaq Ali, Maram Fahhad Almufareh, et al.
Applied Artificial Intelligence (2022) Vol. 36, Iss. 1
Open Access | Times Cited: 49
An interpretable forecasting framework for energy consumption and CO2 emissions
Serkan Aras, M. Hanifi Van
Applied Energy (2022) Vol. 328, pp. 120163-120163
Closed Access | Times Cited: 42
Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection
Debarpan Bhattacharya, Neeraj Sharma, Debottam Dutta, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 31
Estimate the incubation period of coronavirus 2019 (COVID-19)
Ke Men, Yihao Li, Xia Wang, et al.
Computers in Biology and Medicine (2023) Vol. 158, pp. 106794-106794
Open Access | Times Cited: 30
Machine Learning-Based Blood RNA Signature for Diagnosis of Autism Spectrum Disorder
Irena Voinsky, Oleg Y. Fridland, Adi Aran, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 2082-2082
Open Access | Times Cited: 22
AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods
Muhammad Usman Tariq, Shuhaida Ismail
Osong Public Health and Research Perspectives (2024) Vol. 15, Iss. 2, pp. 115-136
Open Access | Times Cited: 12
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