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:

Reliable Breast Cancer Diagnosis with Deep Learning: DCGAN-Driven Mammogram Synthesis and Validity Assessment
Dilawar Shah, Mohammad Asmat Ullah Khan, Mohammad Abrar
Applied Computational Intelligence and Soft Computing (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 7

Showing 7 citing articles:

Advancing Breast Cancer Diagnosis through Breast Mass Images, Machine Learning, and Regression Models
Amira J. Zaylaa, Sylva Kourtian
Sensors (2024) Vol. 24, Iss. 7, pp. 2312-2312
Open Access | Times Cited: 4

Optimizing Breast Cancer Detection With an Ensemble Deep Learning Approach
Dilawar Shah, Mohammad Asmat Ullah Khan, Mohammad Abrar, et al.
International Journal of Intelligent Systems (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 3

Enhancing Grayscale Image Synthesis with Deep Conditional GAN and Transfer Learning
Marya Ryspayeva, Alina Nishan
(2024), pp. 122-127
Closed Access

3D Synthetic View for X-Ray Breast Cancer Mammogram Images
Mohammad Alfraheed
Ingénierie des systèmes d information (2024) Vol. 29, Iss. 4, pp. 1639-1652
Open Access

Breast Cancer Detection Using Transfer Learning with DCGAN for dataset imbalance
M. Meyyappan, Aniket Verma, Ginikunta Sai Karthik Goud, et al.
2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) (2024), pp. 1-5
Closed Access

m5CTNKmer: Identification of 5‐Methylated Base Cytosine of Ribonucleic Acid Using Supervised Machine Learning Techniques
Shahid Qazi, Dilawar Shah, Mohammad A. U. Khan, et al.
Engineering Reports (2024)
Closed Access

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