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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:

Medical image based breast cancer diagnosis: State of the art and future directions
Mehreen Tariq, Sajid Iqbal, Hareem Ayesha, et al.
Expert Systems with Applications (2020) Vol. 167, pp. 114095-114095
Closed Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

Unified deep learning models for enhanced lung cancer prediction with ResNet-50–101 and EfficientNet-B3 using DICOM images
Vinod Kumar, Chander Prabha, Preeti Sharma, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 15
The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions
Arash Heidari, Nima Jafari Navimipour, Mehmet Ünal, et al.
Computers in Biology and Medicine (2021) Vol. 141, pp. 105141-105141
Open Access | Times Cited: 76
Deep convolutional neural networks for computer-aided breast cancer diagnostic: a survey
Parita Oza, Paawan Sharma, Samir Patel, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 3, pp. 1815-1836
Closed Access | Times Cited: 60
Automatic medical image interpretation: State of the art and future directions
Hareem Ayesha, Sajid Iqbal, Mehreen Tariq, et al.
Pattern Recognition (2021) Vol. 114, pp. 107856-107856
Closed Access | Times Cited: 59
A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning
Sema Atasever, Nuh Azgınoglu, Duygu Sinanç Terzi, et al.
Clinical Imaging (2022) Vol. 94, pp. 18-41
Closed Access | Times Cited: 56
Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey
Sarah M. Ayyad, Mohamed Shehata, Ahmed Shalaby, et al.
Sensors (2021) Vol. 21, Iss. 8, pp. 2586-2586
Open Access | Times Cited: 47
Adaptive Threshold Learning in Frequency Domain for Classification of Breast Cancer Histopathological Images
Yujian Liu, Xiaozhang Liu, Yuan Qi
International Journal of Intelligent Systems (2024) Vol. 2024, pp. 1-13
Open Access | Times Cited: 6
Detecting and classifying breast masses via YOLO-based deep learning
Büşra Kübra Karaca, Ziya Telatar, Selda Güney, et al.
Neural Computing and Applications (2025)
Open Access
Automated Computer-Assisted Medical Decision-Making System Based on Morphological Shape and Skin Thickness Analysis for Asymmetry Detection in Mammographic Images
Rafael Bayareh-Mancilla, Luis Alberto Medina-Ramos, Alfonso Toriz-Vázquez, et al.
Diagnostics (2023) Vol. 13, Iss. 22, pp. 3440-3440
Open Access | Times Cited: 15
The power of deep learning for intelligent tumor classification systems: A review
Chandni, Monika Sachdeva, Alok Kumar Singh Kushwaha
Computers & Electrical Engineering (2023) Vol. 106, pp. 108586-108586
Closed Access | Times Cited: 14
Applications of dynamic feature selection and clustering methods to medical diagnosis
Mohammad Mahdi Ershadi, Abbas Seifi
Applied Soft Computing (2022) Vol. 126, pp. 109293-109293
Closed Access | Times Cited: 20
Transfer Learning Based Lightweight Ensemble Model for Imbalanced Breast Cancer Classification
Shankey Garg, Pradeep Singh
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1529-1539
Closed Access | Times Cited: 16
A review of deep learning approaches in clinical and healthcare systems based on medical image analysis
Hadeer A. Helaly, Mahmoud Badawy, Amira Y. Haikal
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 36039-36080
Closed Access | Times Cited: 9
Computer-Aided Breast Cancer Diagnosis: Comparative Analysis of Breast Imaging Modalities and Mammogram Repositories
Parita Oza, Paawan Sharma, Samir Patel, et al.
Current Medical Imaging Formerly Current Medical Imaging Reviews (2022) Vol. 19, Iss. 5, pp. 456-468
Closed Access | Times Cited: 15
Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images
Mohammad Alkhaleefah, Tan-Hsu Tan, Chuan-Hsun Chang, et al.
Cancers (2022) Vol. 14, Iss. 16, pp. 4030-4030
Open Access | Times Cited: 15
Microscopic image analysis in breast cancer detection using ensemble deep learning architectures integrated with web of things
Adlin Sheeba, P. Santhosh Kumar, M. Ramamoorthy, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104048-104048
Closed Access | Times Cited: 14
A novel discrete learning-based intelligent methodology for breast cancer classification purposes
Mehdi Khashei, Negar Bakhtiarvand
Artificial Intelligence in Medicine (2023) Vol. 139, pp. 102492-102492
Closed Access | Times Cited: 8
A systematic review of machine and deep learning techniques for the identification and classification of breast cancer through medical image modalities
Neha Thakur, Pardeep Kumar, A. P. Siva Kumar
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 35849-35942
Closed Access | Times Cited: 8
Comparison of breast cancer classification models on Wisconsin dataset
Rania R. Kadhim, Mohammed Y. Kamil
International Journal of Reconfigurable and Embedded Systems (IJRES) (2022) Vol. 11, Iss. 2, pp. 166-166
Open Access | Times Cited: 13
A transfer learning‐based system for grading breast invasive ductal carcinoma
R. Sujatha, Jyotir Moy Chatterjee, Anastassia Angelopoulou, et al.
IET Image Processing (2022) Vol. 17, Iss. 7, pp. 1979-1990
Open Access | Times Cited: 12
An Innovative Faster R-CNN-Based Framework for Breast Cancer Detection in MRI
João Nuno Centeno Raimundo, João Fontes, Luís Magalhães, et al.
Journal of Imaging (2023) Vol. 9, Iss. 9, pp. 169-169
Open Access | Times Cited: 7
Explainable AI based efficient ensemble model for breast cancer classification using optical coherence tomography
Babita Dhiman, Sangeeta Kamboj, Vishal Srivastava
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 106007-106007
Closed Access | Times Cited: 2
A Comprehensive Study of Mammogram Classification Techniques
Parita Oza, Yash Shah, Marsha Vegda
Intelligent systems reference library (2021), pp. 217-238
Open Access | Times Cited: 15
Spatial neighborhood intensity constraint (SNIC) and knowledge-based clustering framework for tumor region segmentation in breast histopathology images
Xiao Jian Tan, Nazahah Mustafa, ‪Mohd Yusoff Mashor, et al.
Multimedia Tools and Applications (2022) Vol. 81, Iss. 13, pp. 18203-18222
Closed Access | Times Cited: 10
A New Hybrid Breast Cancer Diagnosis Model Using Deep Learning Model and ReliefF
Kadir Can Burçak, Harun Uğuz
Traitement du signal (2022) Vol. 39, Iss. 2, pp. 521-529
Open Access | Times Cited: 10
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