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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:

Compatible-domain Transfer Learning for Breast Cancer Classification with Limited Annotated Data
Mohammad Amin Shamshiri, Adam Krzyżak, Marek Kowal, et al.
Computers in Biology and Medicine (2023) Vol. 154, pp. 106575-106575
Closed Access | Times Cited: 11

Showing 11 citing articles:

Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives
Suruchi Kumari, Pravendra Singh
Computers in Biology and Medicine (2023) Vol. 170, pp. 107912-107912
Open Access | Times Cited: 18
Federated and transfer learning for cancer detection based on image analysis
Amine Bechar, Rafik Medjoudj, Youssef Elmir, et al.
Neural Computing and Applications (2025)
Open Access
HAFMAB-Net: hierarchical adaptive fusion based on multilevel attention-enhanced bottleneck neural network for breast histopathological cancer classification
Ali H. Abdulwahhab, Oğuz Bayat, Abdullahi Abdu İbrahim
Signal Image and Video Processing (2025) Vol. 19, Iss. 5
Closed Access
Diffuse tumors: Molecular determinants shared by different cancer types
Xuan Li, Dingyun Liu, Zhipeng Wu, et al.
Computers in Biology and Medicine (2024) Vol. 178, pp. 108703-108703
Open Access | Times Cited: 1
Reversed domain adaptation for nuclei segmentation-based pathological image classification
Zhixin Xu, Seohoon Lim, Yucheng Lu, et al.
Computers in Biology and Medicine (2023) Vol. 168, pp. 107726-107726
Closed Access | Times Cited: 2
Generative adversarial network: a statistical-based deep learning paradigm to improve detecting breast cancer in thermograms
Seyed Vahab Shojaedini, Mehdi Abedini, Mahsa Monajemi
Medical & Biological Engineering & Computing (2023) Vol. 62, Iss. 4, pp. 1077-1087
Closed Access | Times Cited: 2
Exploring the Potential of Transfer Learning for Accurate Segmentation of Pathological Structures in X-Ray Images
Lalit Kishore, Mubeen Shaikh, Pawan Kumar Goel, et al.
(2024), pp. 769-774
Closed Access
Lychee cultivar fine-grained image classification method based on improved ResNet-34 residual network
Yiming Xiao, Jianhua Wang, Hongyi Xiong, et al.
Journal of Agricultural Engineering (2024)
Open Access
A new method for promoting the detection of breast cancer in thermograms: applying deep autoencoders for eliminating redundancies in parallel with preserving independent components
Seyed Vahab Shojaedini, Bahram Bahramzadeh
Journal of Ambient Intelligence and Humanized Computing (2024) Vol. 15, Iss. 12, pp. 4085-4099
Closed Access
The AI Revolution: Deep Learning’s Role in Abdominal Trauma Detection
G. Jothi, Ahmad Taher Azar, Nashwa Ahmad Kamal, et al.
Lecture notes on data engineering and communications technologies (2024), pp. 303-316
Closed Access
Breast Cancer Identification and Classification Using Contextual Deep Learning Technique in Histopathological Images
G N Keshava Murthy, Piyush Kumar Pareek, C P Nayana, et al.
(2023), pp. 1-7
Closed Access
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