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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:

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: 21

Showing 21 citing articles:

Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
Silvia Seoni, Jahmunah Vicnesh, Massimo Salvi, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107441-107441
Open Access | Times Cited: 84
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: 16
A novel ensemble learning framework based on a genetic algorithm for the classification of pneumonia
Mahır Kaya, Yasemın Çetın-Kaya
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108494-108494
Closed Access | Times Cited: 12
Attention-map augmentation for hypercomplex breast cancer classification
Eleonora Lopez, Filippo Betello, Federico Carmignani, et al.
Pattern Recognition Letters (2024) Vol. 182, pp. 140-146
Open Access | Times Cited: 10
Feature fusion-based ensemble CNN learning optimization for automated detection of pediatric pneumonia
Mahır Kaya
Biomedical Signal Processing and Control (2023) Vol. 87, pp. 105472-105472
Closed Access | Times Cited: 21
Using PBL and Agile to Teach Artificial Intelligence to Undergraduate Computing Students
Vitor Augusto Menten de Barros, Henrique Mohallem Paiva, Victor Takashi Hayashi
IEEE Access (2023) Vol. 11, pp. 77737-77749
Open Access | Times Cited: 12
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
CICADA (UCX): A Novel Approach for Automated Breast Cancer Classification through Aggressiveness Delineation
Davinder Paul Singh, Tathagat Banerjee, Prabhjot Kour, et al.
Computational Biology and Chemistry (2025) Vol. 115, pp. 108368-108368
Closed Access
Hybrid convolutional neural network and bi-LSTM model with EfficientNet-B0 for high-accuracy breast cancer detection and classification
Umesh Kumar Lilhore, Yogesh Kumar Sharma, Brajesh Kumar Shukla, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A Multi-stage Optimization Architecture for Effective Breast Cancer Diagnosis Based on Deep Neural Networks
Tawfiq Beghriche, Youcef Brik, Mohamed Djerioui, et al.
Arabian Journal for Science and Engineering (2025)
Closed Access
Etemadi reliability-based multi-layer perceptrons for classification and forecasting
Sepideh Etemadi, Mehdi Khashei, Saba Tamizi
Information Sciences (2023) Vol. 651, pp. 119716-119716
Closed Access | Times Cited: 7
Optimized Bayesian convolutional neural networks for invasive breast cancer diagnosis system
Dalia Ezzat, Aboul Ella Hassanien
Applied Soft Computing (2023) Vol. 147, pp. 110810-110810
Closed Access | Times Cited: 6
PLA—A Privacy-Embedded Lightweight and Efficient Automated Breast Cancer Accurate Diagnosis Framework for the Internet of Medical Things
Chengxiao Yan, Xiaoyang Zeng, Rui Xi, et al.
Electronics (2023) Vol. 12, Iss. 24, pp. 4923-4923
Open Access | Times Cited: 3
The prediction of NICU admission and identifying influential factors in four different categories leveraging machine learning approaches
Reza Tashakkori, Ashkan Mozdgir, Atena Karimi, et al.
Biomedical Signal Processing and Control (2023) Vol. 90, pp. 105844-105844
Closed Access | Times Cited: 2
Data-Driven Breast Cancer Diagnosis: a Comparative Study
Dalya Abdulqader Mohammed, Wisam Dawood Abdullah, Ahmad Ghandour
Lecture notes in networks and systems (2024), pp. 667-681
Closed Access
Generalisation and reliability of deep learning for digital pathology in a clinical setting
Milda Pocevičiūtė
Linköping studies in science and technology. Dissertations (2023)
Open Access | Times Cited: 1
An interpretable Bayesian deep learning-based approach for sustainable clean energy
Dalia Ezzat, Eman Ahmed, Mona Soliman, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 27, pp. 17145-17163
Open Access
Bayesian Optimized Artificial Neural Network for Breast Cancer Classification
Nayan Kajal Rout, Lingraj Dora, Sanjay Agrawal
2022 International Conference on Inventive Computation Technologies (ICICT) (2024)
Closed Access
Uncertainty-Aware Deep Learning Classification for MRI-Based Prostate Cancer Detection
Kamilia Taguelmimt, Hong-Phuong Dang, Gustavo Miranda, et al.
Lecture notes in computer science (2024), pp. 114-123
Closed Access
A framework for robust glaucoma detection: A confidence-aware deep uncertainty quantification approach with a comprehensive assessment for enhanced clinical decision-making
Javad Zarean, AmirReza Tajally, Reza Tavakkoli‐Moghaddam, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109651-109651
Closed Access
Enhancing Breast Cancer Diagnosis using a Modified Elman Neural Network with Optimized Algorithm Integration
Linkai Chen, CongZhe You, Honghui Fan, et al.
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 9
Open Access
A Novel Deep Learning Approach to Malaria Disease Detection on Two Malaria Datasets
İbrahim ÇETİNER, Halit ÇETİNER
Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi (2023) Vol. 10, Iss. 2, pp. 254-272
Open Access
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