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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:

Predicting Invasive Disease-Free Survival for Early Stage Breast Cancer Patients Using Follow-Up Clinical Data
Bo Fu, Pei Liu, Jie Lin, et al.
IEEE Transactions on Biomedical Engineering (2018) Vol. 66, Iss. 7, pp. 2053-2064
Closed Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Federated learning aided breast cancer detection with intelligent Heuristic-based deep learning framework
Savita Kumbhare, Atul B. Kathole, Swati Shinde
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105080-105080
Closed Access | Times Cited: 50
Optimizing Survival Analysis of XGBoost for Ties to Predict Disease Progression of Breast Cancer
Pei Liu, Bo Fu, Simon X. Yang, et al.
IEEE Transactions on Biomedical Engineering (2020) Vol. 68, Iss. 1, pp. 148-160
Closed Access | Times Cited: 115
Predicting breast cancer 5-year survival using machine learning: A systematic review
Jiaxin Li, Zijun Zhou, Jianyu Dong, et al.
PLoS ONE (2021) Vol. 16, Iss. 4, pp. e0250370-e0250370
Open Access | Times Cited: 92
Fuzzy Neural Network Expert System with an Improved Gini Index Random Forest-Based Feature Importance Measure Algorithm for Early Diagnosis of Breast Cancer in Saudi Arabia
Ebrahem A. Algehyne, L. J. Muhammad, Naseh A. Algehainy, et al.
Big Data and Cognitive Computing (2022) Vol. 6, Iss. 1, pp. 13-13
Open Access | Times Cited: 51
A Systematic Review on Breast Cancer Detection Using Deep Learning Techniques
Kamakshi Rautela, Dinesh Kumar, Vijay Kumar
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 7, pp. 4599-4629
Closed Access | Times Cited: 42
A Comparative Study of Machine Learning Algorithms for Detecting Breast Cancer
Razib Hayat Khan, Jonayet Miah, Md Minhazur Rahman, et al.
2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) (2023), pp. 647-652
Closed Access | Times Cited: 35
Enhancing Digital Health Services with Big Data Analytics
Nisrine Berros, Fatna Elmendili, Youness Filaly, et al.
Big Data and Cognitive Computing (2023) Vol. 7, Iss. 2, pp. 64-64
Open Access | Times Cited: 34
Analyzing breast cancer invasive disease event classification through explainable artificial intelligence
Raffaella Massafra, Annarita Fanizzi, Nicola Amoroso, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 25
Artificial intelligence auxiliary diagnosis and treatment system for breast cancer in developing countries
Wenxiu Li, Fangfang Gou, Jia Wu
Journal of X-Ray Science and Technology (2024) Vol. 32, Iss. 2, pp. 395-413
Closed Access | Times Cited: 15
Artificial Intelligence Breakthroughs in Pioneering Early Diagnosis and Precision Treatment of Breast Cancer: A Multimethod Study
Mohammad Reza Darbandi, Mahsa Darbandi, Sara Darbandi, et al.
European Journal of Cancer (2024) Vol. 209, pp. 114227-114227
Closed Access | Times Cited: 10
DSCA: A dual-stream network with cross-attention on whole-slide image pyramids for cancer prognosis
Pei Liu, Bo Fu, Feng Ye, et al.
Expert Systems with Applications (2023) Vol. 227, pp. 120280-120280
Open Access | Times Cited: 22
An Explainable AI Approach for Breast Cancer Metastasis Prediction Based on Clinicopathological Data
Ikram Maouche, Labib Sadek Terrissa, K. Benmohammed, et al.
IEEE Transactions on Biomedical Engineering (2023) Vol. 70, Iss. 12, pp. 3321-3329
Closed Access | Times Cited: 21
Classification of breast cancer mammogram images using convolution neural network
Umar Albalawi, S. Manimurugan, R. Varatharajan
Concurrency and Computation Practice and Experience (2020) Vol. 34, Iss. 13
Closed Access | Times Cited: 42
Lightweight Privacy-Preserving Medical Diagnosis in Edge Computing
Zhuoran Ma, Jianfeng Ma, Yinbin Miao, et al.
IEEE Transactions on Services Computing (2020) Vol. 15, Iss. 3, pp. 1606-1618
Closed Access | Times Cited: 42
Convolutional neural network with parallel convolution scale attention module and ResCBAM for breast histology image classification
Ting Yan, Guohui Chen, Huimin Zhang, et al.
Heliyon (2024) Vol. 10, Iss. 10, pp. e30889-e30889
Open Access | Times Cited: 6
Development and assessment of machine learning algorithms for predicting remission after transsphenoidal surgery among patients with acromegaly
Yanghua Fan, Yansheng Li, Yichao Li, et al.
Endocrine (2019) Vol. 67, Iss. 2, pp. 412-422
Closed Access | Times Cited: 39
Machine Learning model for Breast Cancer Prediction
Ankur Gupta, Dushyant Kaushik, Muskan Garg, et al.
2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) (2020), pp. 472-477
Closed Access | Times Cited: 37
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
Laura Macías‐García, M. Martínez-Ballesteros, José María Luna-Romera, et al.
Artificial Intelligence in Medicine (2020) Vol. 110, pp. 101976-101976
Open Access | Times Cited: 36
Development of Machine Learning Models for Predicting Postoperative Delayed Remission in Patients With Cushing’s Disease
Yanghua Fan, Yichao Li, Xinjie Bao, et al.
The Journal of Clinical Endocrinology & Metabolism (2020) Vol. 106, Iss. 1, pp. e217-e231
Open Access | Times Cited: 28
Prediction of postoperative recovery in patients with acoustic neuroma using machine learning and SMOTE-ENN techniques
Jianing Wang
Mathematical Biosciences & Engineering (2022) Vol. 19, Iss. 10, pp. 10407-10423
Open Access | Times Cited: 19
Artificial intelligence-based preoperative prediction system for diagnosis and prognosis in epithelial ovarian cancer: A multicenter study
Meixuan Wu, Yaqian Zhao, Xuhui Dong, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 18
Combining Traditional Analysis and Machine Learning to Predict Early, Middle, and Long-term Recurrence of Intrahepatic Cholangiocarcinoma
Ruoyu Zhang, Zengshuai Wang, Min Yang, et al.
European Journal of Surgical Oncology (2025), pp. 110141-110141
Closed Access
Construction of an indoor radio environment map using gradient boosting decision tree
Syahidah Izza Rufaida, Jenq‐Shiou Leu, Kuan‐Wu Su, et al.
Wireless Networks (2020) Vol. 26, Iss. 8, pp. 6215-6236
Closed Access | Times Cited: 24
Detection of breast cancer by deep belief network with improved activation function
S. Archana
International Journal of Adaptive Control and Signal Processing (2024) Vol. 38, Iss. 9, pp. 3074-3101
Closed Access | Times Cited: 3
Approximated Ensemble Learning Driven Boosting Method for Breast Cancer Prediction on Multi-modal Clinical Datasets
K. Anguraju, C. Puvanadevi, R. Kirthiga, et al.
Lecture notes in networks and systems (2025), pp. 1-14
Closed Access
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