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:

Explainable machine learning for breast cancer diagnosis from mammography and ultrasound images: a systematic review
Daraje Kaba Gurmessa, Worku Jimma
BMJ Health & Care Informatics (2024) Vol. 31, Iss. 1, pp. e100954-e100954
Open Access | Times Cited: 9

Showing 9 citing articles:

Decoding the black box: Explainable AI (XAI) for cancer diagnosis, prognosis, and treatment planning-A state-of-the art systematic review
Youssef Alaaeldin Ali Mohamed, Bee Luan Khoo, Mohd Shahrimie Mohd Asaari, et al.
International Journal of Medical Informatics (2024) Vol. 193, pp. 105689-105689
Closed Access | Times Cited: 5
Computer-aided cholelithiasis diagnosis using explainable convolutional neural network
Dheeraj Kumar, Mayuri A. Mehta, Ketan Kotecha, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Evaluating the Effectiveness of Explainable AI Techniques in Interpreting Breast Cancer Diagnoses Across Multiple Imaging Modalities
禄 李
Advances in Clinical Medicine (2025) Vol. 15, Iss. 02, pp. 1503-1512
Closed Access
Artificial Intelligence for Ovarian Cancer Detection with Medical Images: A Review of the Last Decade (2013–2023)
Amir Reza Naderi Yaghouti, Ahmad Shalbaf, Roohallah Alizadehsani, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
Revolutionizing breast ultrasound diagnostics with EfficientNet-B7 and Explainable AI
M. Latha, P. Santhosh Kumar, R. Roopa Chandrika, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Analyzing the Performance of Explainable Machine Learning Models in Risk Factor Identification for Major Cancers (Preprint)
Xiayuan Huang
(2024)
Open Access
Anais do Simpósio Brasileiro de Inteligência Artificial
Milena Rodrigues Pontes, M Damasceno, Gabriela Lais da Silva, et al.
Editora Pascal LTDA eBooks (2024)
Open Access
Unravelling the recent developments in applications and challenges of AI in cancer biology: An overview
K.K. Ajeeshkumar, Peruvazhipurath Appu Aneesh, Ankita Sahu, et al.
Elsevier eBooks (2024), pp. 125-146
Closed Access
Architecture of a Computer Decision Support System for CADx Breast Cancer
О.О. Aziukovskyi, Volodymyr Hnatushenko, В. Ф. Завізіон, et al.
Lecture notes on data engineering and communications technologies (2024), pp. 410-430
Closed Access
Leveraging Explainable Machine Learning to Uncover the Association between Risk Factors and Major Cancers: Cancer Risk Factor Association Study (Preprint)
Xiayuan Huang, Shan Ren, Xufeng Mao, et al.
JMIR Cancer (2024)
Open Access
Page 1

Scroll to top