Open Access Helper

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:

Deep learning in breast radiology: current progress and future directions
William C. Ou, Dogan S. Polat, Başak E. Doğan
European Radiology (2021) Vol. 31, Iss. 7, pp. 4872-4885
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI
Zijian Zhou, Beatriz E. Adrada, Rosalind P. Candelaria, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 24
External Validation of an Ensemble Model for Automated Mammography Interpretation by Artificial Intelligence
William Hsu, Daniel S. Hippe, Noor Nakhaei, et al.
JAMA Network Open (2022) Vol. 5, Iss. 11, pp. e2242343-e2242343
Open Access | Times Cited: 29
Ultrasonography and clinicopathological features of breast cancer in predicting axillary lymph node metastases
Jiajia Xiong, Wei Zuo, Yu Wu, et al.
BMC Cancer (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 27
Barriers and facilitators of artificial intelligence conception and implementation for breast imaging diagnosis in clinical practice: a scoping review
Belinda Lokaj, Marie‐Thérèse Pugliese, Karen Kinkel, et al.
European Radiology (2023) Vol. 34, Iss. 3, pp. 2096-2109
Open Access | Times Cited: 13
Beyond high hopes: A scoping review of the 2019–2021 scientific discourse on machine learning in medical imaging
Vasileios Nittas, Paola Daniore, Constantin Landers, et al.
PLOS Digital Health (2023) Vol. 2, Iss. 1, pp. e0000189-e0000189
Open Access | Times Cited: 12
Deep learning-based classification of breast lesions using dynamic ultrasound video
Guojia Zhao, Dezhuag Kong, Xiangli Xu, et al.
European Journal of Radiology (2023) Vol. 165, pp. 110885-110885
Closed Access | Times Cited: 12
Influence of the Computer-Aided Decision Support System Design on Ultrasound-Based Breast Cancer Classification
Zuzanna Magnuska, Benjamin Theek, Milita Darguzyte, et al.
Cancers (2022) Vol. 14, Iss. 2, pp. 277-277
Open Access | Times Cited: 20
An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions
Lijun Wang, Lufan Chang, Ran Luo, et al.
European Radiology (2022) Vol. 32, Iss. 7, pp. 4857-4867
Closed Access | Times Cited: 19
Transition of traditional method to deep learning based computer-aided system for breast cancer using Automated Breast Ultrasound System (ABUS) images: a review
D. Mohamad, Syamsiah Mashohor, Rozi Mahmud, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. 12, pp. 15271-15300
Closed Access | Times Cited: 11
Artificial Intelligence (AI) in Breast Imaging: A Scientometric Umbrella Review
Xiao Jian Tan, Wai Loon Cheor, Li Li Lim, et al.
Diagnostics (2022) Vol. 12, Iss. 12, pp. 3111-3111
Open Access | Times Cited: 18
A review of artificial intelligence in mammography
Meghan P. Jairam, Richard Ha
Clinical Imaging (2022) Vol. 88, pp. 36-44
Closed Access | Times Cited: 17
Development and validation of a deep learning model for breast lesion segmentation and characterization in multiparametric MRI
Jingjin Zhu, Jiahui Geng, W. Shan, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 15
The utilization of artificial intelligence applications to improve breast cancer detection and prognosis
Walaa Alsharif
Saudi Medical Journal (2023) Vol. 44, Iss. 2, pp. 119-127
Open Access | Times Cited: 7
Artificial Intelligence-Enhanced Breast MRI
Roberto Lo Gullo, Eric Marcus, Jorge Huayanay, et al.
Investigative Radiology (2023) Vol. 59, Iss. 3, pp. 230-242
Open Access | Times Cited: 7
Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography
Ming Ni, Lixiang Gao, Wen Chen, et al.
International Orthopaedics (2023) Vol. 48, Iss. 1, pp. 183-191
Open Access | Times Cited: 5
Multi-Task Fusion for Improving Mammography Screening Data Classification
M Wimmer, Gert Sluiter, David Major, et al.
IEEE Transactions on Medical Imaging (2021) Vol. 41, Iss. 4, pp. 937-950
Open Access | Times Cited: 13
Leveraging Multi-Task Learning to Cope With Poor and Missing Labels of Mammograms
Mickael Tardy, Diana Mateus
Frontiers in Radiology (2022) Vol. 1
Open Access | Times Cited: 9
A generalized optimization-based generative adversarial network
Bahram Farhadinia, Mohammad Reza Ahangari, Aghileh Heydari, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123413-123413
Open Access | Times Cited: 1
Detailed Image Data Quality and Cleaning Practices for Artificial Intelligence Tools for Breast Cancer
D. Y. Wu, Yisheng Fang, Dat T. Vo, et al.
JCO Clinical Cancer Informatics (2024), Iss. 8
Closed Access | Times Cited: 1
Breast Cancer: The Road to a Personalized Prevention
Grattagliano Zaira, Grattagliano Asia
IgMin Research (2024) Vol. 2, Iss. 3, pp. 163-170
Open Access | Times Cited: 1
Predicting Pathological Characteristics of HER2-Positive Breast Cancer from Ultrasound Images: a Deep Ensemble Approach
Zhihui Chen, Hailing Zha, Qing Yao, et al.
Deleted Journal (2024)
Closed Access | Times Cited: 1
Artificial Intelligence in Breast Imaging
Xin Wang, Nikita Moriakov, Yuan Gao, et al.
Medical radiology (2022), pp. 435-453
Open Access | Times Cited: 5
EPD: an integrated modeling technique to classify BC
Sashikanta Prusty, Sujit Kumar Dash, Srikanta Patnaik, et al.
2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT) (2023), pp. 651-655
Closed Access | Times Cited: 2
Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs
Zijian Zhou, Beatriz E. Adrada, Rosalind P. Candelaria, et al.
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2023), pp. 1-4
Closed Access | Times Cited: 2
Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors
Emrah Gündüz, Ömer Faruk Alçin, Ahmet Kızılay, et al.
Current Opinion in Otolaryngology & Head & Neck Surgery (2021) Vol. 30, Iss. 2, pp. 107-113
Closed Access | Times Cited: 6
Page 1 - Next Page

Scroll to top