OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Neural network model based on global and local features for multi-view mammogram classification
Lili Xia, Jianpeng An, Chao Ma, et al.
Neurocomputing (2023) Vol. 536, pp. 21-29
Closed Access | Times Cited: 14

Showing 14 citing articles:

Inspired by “Focus, Fusion, Collaboration”: A multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images
Linna Zhao, Jianqiang Li, Qing Zhao, et al.
Expert Systems with Applications (2025), pp. 126806-126806
Closed Access | Times Cited: 1

An intelligent healthcare framework for breast cancer diagnosis based on the information fusion of novel deep learning architectures and improved optimization algorithm
Kiran Jabeen, Muhammad Attique Khan, Robertas Damaševičius, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 137, pp. 109152-109152
Closed Access | Times Cited: 7

MV-MS-FETE: Multi-view multi-scale feature extractor and transformer encoder for stenosis recognition in echocardiograms
Danilo Avola, Irene Cannistraci, Marco Cascio, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 245, pp. 108037-108037
Open Access | Times Cited: 6

Mv-Trams: An Efficient Tumor Region-Adapted Mammography Synthesis Under Multi-View Diagnosis
Huy T. Nguyen, Thinh B. Lam, Thuy Thanh Truong, et al.
(2025)
Closed Access

Hybrid transformer‐based model for mammogram classification by integrating prior and current images
Afsana Ahsan Jeny, Sahand Hamzehei, Annie Jin, et al.
Medical Physics (2025) Vol. 52, Iss. 5, pp. 2999-3014
Closed Access

An Intelligent Approach for Automating Robotic Arm Maneuvering in Endometriosis Surgery
Sina Saadati, Maryam Hashemi
Research Square (Research Square) (2025)
Closed Access

Within- cross- consensus-view representation-based multi-view multi-label learning with incomplete data
Changming Zhu, Yanchen Liu, Duoqian Miao, et al.
Neurocomputing (2023) Vol. 557, pp. 126729-126729
Closed Access | Times Cited: 9

WS-MTST: Weakly Supervised Multi-Label Brain Tumor Segmentation With Transformers
Huazhen Chen, Jianpeng An, Bochang Jiang, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 12, pp. 5914-5925
Closed Access | Times Cited: 6

Multiple Multi-Modal Methods of Malignant Mammogram Classification
Christopher Vattheuer, Nguyen Tran, Carson K. Leung, et al.
2022 IEEE 10th International Conference on Healthcare Informatics (ICHI) (2024), pp. 57-66
Closed Access | Times Cited: 1

A Systematic Literature Review on Mammography: Deep Learning in Redefining Breast Cancer Diagnosis for the Asian Perspective
Ashwini Amin, U. Dinesh Acharya, P. C. Siddalingaswamy, et al.
Research Square (Research Square) (2024)
Open Access

Multi-modal classification of breast cancer lesions in Digital Mammography and contrast enhanced spectral mammography images
Narjes Bouzarjomehri, Mohammad Barzegar, Habib Rostami, et al.
Computers in Biology and Medicine (2024) Vol. 183, pp. 109266-109266
Closed Access

Breast Cancer Diagnosis Method Based on Cross-Mammogram Four-View Interactive Learning
Xuesong Wen, Jianjun Li, Liyuan Yang
Tomography (2024) Vol. 10, Iss. 6, pp. 848-868
Open Access

FCC-FMLO and FLeft-FRight: two novel multi-view fusion techniques for breast density assessment from mammograms
Nassima Dif, Mohamed El Amine Boudinar, Mohamed Amine Abdelali, et al.
Multimedia Tools and Applications (2024)
Closed Access

Segmentation-Based Classification Deep Learning Model for Breast Cancer Detection using Mammogram images
Ankita Sinha, Manjusha Pandey, M. Nazma B. J. Naskar, et al.
(2023), pp. 1-8
Closed Access

Page 1

Scroll to top