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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:

Objective evaluation of deep uncertainty predictions for COVID-19 detection
Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir, et al.
Biomedical Signal Processing and Control (2021) Vol. 68, pp. 102622-102622
Open Access | Times Cited: 157
Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods
Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani, et al.
Results in Physics (2021) Vol. 27, pp. 104495-104495
Open Access | Times Cited: 131
Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020)
Roohallah Alizadehsani, Mohamad Roshanzamir, Sadiq Hussain, et al.
Annals of Operations Research (2021) Vol. 339, Iss. 3, pp. 1077-1118
Open Access | Times Cited: 102
Combining a convolutional neural network with autoencoders to predict the survival chance of COVID-19 patients
Fahime Khozeimeh, Danial Sharifrazi, Navid Hoseini Izadi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 102
Machine learning applications for COVID-19 outbreak management
Arash Heidari, Nima Jafari Navimipour, Mehmet Ünal, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 18, pp. 15313-15348
Open Access | Times Cited: 91
Automated detection and forecasting of COVID-19 using deep learning techniques: A review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, et al.
Neurocomputing (2024) Vol. 577, pp. 127317-127317
Open Access | Times Cited: 46
Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis
Benjamin Lambert, Florence Forbes, Senan Doyle, et al.
Artificial Intelligence in Medicine (2024) Vol. 150, pp. 102830-102830
Open Access | Times Cited: 45
A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods
Ling Huang, Su Ruan, Yucheng Xing, et al.
Medical Image Analysis (2024) Vol. 97, pp. 103223-103223
Open Access | Times Cited: 15
Artificial Intelligence and Internet of Things (AI-IoT) Technologies in Response to COVID-19 Pandemic: A Systematic Review
Junaid Iqbal Khan, Jebran Khan, Furqan Ali, et al.
IEEE Access (2022) Vol. 10, pp. 62613-62660
Open Access | Times Cited: 53
Uncertainty quantification in DenseNet model using myocardial infarction ECG signals
Jahmunah Vicnesh, E. Y. K. Ng, Ru San Tan, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 229, pp. 107308-107308
Open Access | Times Cited: 47
Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images
L. Calefice, Shengxiang Yang, Armaghan Moemeni, et al.
IEEE Access (2021) Vol. 9, pp. 85442-85454
Open Access | Times Cited: 40
COVID-19 Prediction Using Black-Box Based Pearson Correlation Approach
Dilber Uzun Ozsahin, Efe Precious Onakpojeruo, Basil Bartholomew Duwa, et al.
Diagnostics (2023) Vol. 13, Iss. 7, pp. 1264-1264
Open Access | Times Cited: 16
Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram
Marília Barandas, Lorenzo Famiglini, Andrea Campagner, et al.
Information Fusion (2023) Vol. 101, pp. 101978-101978
Open Access | Times Cited: 15
Data-driven prediction and uncertainty quantification of PWR Crud-Induced Power Shift using convolutional neural networks
Aidan Furlong, Farah Alsafadi, Scott Palmtag, et al.
Energy (2025), pp. 134447-134447
Open Access
Deep uncertainty quantification algorithms for confidence-aware hope classification of breast cancer patients based on their cognitive features
AmirReza Tajally, Javad Zarean Dowlat Abadi, Ali Bozorgi-Amiri, et al.
Applied Soft Computing (2025), pp. 112860-112860
Closed Access
COVID-19 chest X-ray detection through blending ensemble of CNN snapshots
Avinandan Banerjee, Arya Sarkar, Sayantan Roy, et al.
Biomedical Signal Processing and Control (2022) Vol. 78, pp. 104000-104000
Open Access | Times Cited: 26
Breast Cancer Dataset, Classification and Detection Using Deep Learning
Muhammad Shahid Iqbal, Waqas Ahmad, Roohallah Alizadehsani, et al.
Healthcare (2022) Vol. 10, Iss. 12, pp. 2395-2395
Open Access | Times Cited: 22
Body composition predicts hypertension using machine learning methods: a cohort study
Mohammad Ali Nematollahi, Soodeh Jahangiri, Arefeh Asadollahi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Identification of Clinical Features Associated with Mortality in COVID-19 Patients
Rahimeh Eskandarian, Roohallah Alizadehsani, Mohaddeseh Behjati, et al.
Operations Research Forum (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 12
Uncertainty-aware image classification on 3D CT lung
Rahimi Zahari, Julie Cox, Bogusław Obara
Computers in Biology and Medicine (2024) Vol. 172, pp. 108324-108324
Open Access | Times Cited: 4
Breast cancer classification by a new approach to assessing deep neural network-based uncertainty quantification methods
Fatemeh Hamedani-KarAzmoudehFar, Reza Tavakkoli‐Moghaddam, AmirReza Tajally, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104057-104057
Closed Access | Times Cited: 20
Factors associated with mortality in hospitalized cardiovascular disease patients infected with COVID‐19
Roohallah Alizadehsani, Rahimeh Eskandarian, Mohaddeseh Behjati, et al.
Immunity Inflammation and Disease (2022) Vol. 10, Iss. 3
Open Access | Times Cited: 19
LiteCovidNet: A lightweight deep neural network model for detection of COVID‐19 using X‐ray images
Sachin Kumar, Sourabh Shastri, Shilpa Mahajan, et al.
International Journal of Imaging Systems and Technology (2022) Vol. 32, Iss. 5, pp. 1464-1480
Open Access | Times Cited: 19
Transfer learning with spinally shared layers
H M Dipu Kabir, Subrota Kumar Mondal, Syed Bahauddin Alam, et al.
Applied Soft Computing (2024) Vol. 163, pp. 111908-111908
Open Access | Times Cited: 3
Overhead Reduction Technique for Software-Defined Network Based Intrusion Detection Systems
Ahmed H. Janabi, Triantafyllos Kanakis, Mark Johnson
IEEE Access (2022) Vol. 10, pp. 66481-66491
Open Access | Times Cited: 15
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