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:

A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans
Νικόλαος Παπανδριανός, Elpiniki I. Papageorgiou, Athanasios Anagnostis, et al.
Applied Sciences (2020) Vol. 10, Iss. 3, pp. 997-997
Open Access | Times Cited: 74

Showing 1-25 of 74 citing articles:

Application of Deep Learning in Breast Cancer Imaging
Luuk Balkenende, Jonas Teuwen, Ritse M. Mann
Seminars in Nuclear Medicine (2022) Vol. 52, Iss. 5, pp. 584-596
Open Access | Times Cited: 94
Breast cancer detection using deep learning techniques: challenges and future directions
Muhammad Shahid, Azhar Imran
Multimedia Tools and Applications (2025)
Closed Access | Times Cited: 2
Deep Learning and Machine Learning with Grid Search to Predict Later Occurrence of Breast Cancer Metastasis Using Clinical Data
Xia Jiang, Chuhan Xu
Journal of Clinical Medicine (2022) Vol. 11, Iss. 19, pp. 5772-5772
Open Access | Times Cited: 62
The Role of Deep Learning in Advancing Breast Cancer Detection Using Different Imaging Modalities: A Systematic Review
Mohammad Madani, Mohammad Mahdi Behzadi, Sheida Nabavi
Cancers (2022) Vol. 14, Iss. 21, pp. 5334-5334
Open Access | Times Cited: 50
ChatGPT and large language models in orthopedics: from education and surgery to research
Srijan Chatterjee, Manojit Bhattacharya, Soumen Pal, et al.
Journal of Experimental Orthopaedics (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 35
Medical Image Classifications Using Convolutional Neural Networks: A Survey of Current Methods and Statistical Modeling of the Literature
Foziya Ahmed Mohammed, Kula Kekeba Tune, Beakal Gizachew Assefa, et al.
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 1, pp. 699-736
Open Access | Times Cited: 10
BCDNet: A Deep Learning Model with Improved Convolutional Neural Network for Efficient Detection of Bone Cancer Using Histology Images
Bheemsain Rao, K. Reddy Madhavi
International Journal of Computational and Experimental Science and Engineering (2024) Vol. 10, Iss. 4
Open Access | Times Cited: 8
Applications of artificial intelligence in nuclear medicine image generation
Zhibiao Cheng, Junhai Wen, Gang Huang, et al.
Quantitative Imaging in Medicine and Surgery (2021) Vol. 11, Iss. 6, pp. 2792-2822
Open Access | Times Cited: 41
Machine learning and deep learning for cancer diagnosis
Taiwo Soewu, Harpreet Kaur, Ramandeep Sandhu, et al.
Elsevier eBooks (2025), pp. 83-129
Closed Access
From Segmentation to Biomarker Quantification: A Deep Learning Framework for Metastases Detection in Bone Scans
Ema Rachmawati, M. Rifqi Dzaky Azhad, Ida Bagus Indrabudhi Kusuma, et al.
(2025)
Closed Access
Deep learning in nuclear medicine: from imaging to therapy
Meng-Xin Zhang, Pengfei Liu, Mengdi Zhang, et al.
Annals of Nuclear Medicine (2025)
Closed Access
Diagnostic performance of deep learning models for detecting bone metastasis on whole-body bone scan in prostate cancer
Sangwon Han, Jungsu S. Oh, Jong Jin Lee
European Journal of Nuclear Medicine and Molecular Imaging (2021) Vol. 49, Iss. 2, pp. 585-595
Closed Access | Times Cited: 37
Artificial intelligence-based analysis of whole-body bone scintigraphy: The quest for the optimal deep learning algorithm and comparison with human observer performance
Ghasem Hajianfar, Maziar Sabouri, Yazdan Salimi, et al.
Zeitschrift für Medizinische Physik (2023) Vol. 34, Iss. 2, pp. 242-257
Open Access | Times Cited: 13
Automatic Diagnosis of Coronary Artery Disease in SPECT Myocardial Perfusion Imaging Employing Deep Learning
Νικόλαος Παπανδριανός, Elpiniki I. Papageorgiou
Applied Sciences (2021) Vol. 11, Iss. 14, pp. 6362-6362
Open Access | Times Cited: 31
Segmentation of lung cancer-caused metastatic lesions in bone scan images using self-defined model with deep supervision
Yongchun Cao, Liangxia Liu, Xiaohong Chen, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104068-104068
Open Access | Times Cited: 21
Deep Learning-Based Automated Diagnosis for Coronary Artery Disease Using SPECT-MPI Images
Νικόλαος Παπανδριανός, Anna Feleki, Elpiniki I. Papageorgiou, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 13, pp. 3918-3918
Open Access | Times Cited: 20
Diagnosis of Coronary Artery Disease from Myocardial Perfusion Imaging Using Convolutional Neural Networks
Vincent Peter C. Magboo, Ma. Sheila A. Magboo
Procedia Computer Science (2023) Vol. 218, pp. 810-817
Open Access | Times Cited: 11
BM-Seg: A new bone metastases segmentation dataset and ensemble of CNN-based segmentation approach
Marwa Afnouch, Olfa Gaddour, Yosr Hentati, et al.
Expert Systems with Applications (2023) Vol. 228, pp. 120376-120376
Open Access | Times Cited: 11
A Lightweight Convolutional Neural Network Architecture Applied for Bone Metastasis Classification in Nuclear Medicine: A Case Study on Prostate Cancer Patients
Charis Ntakolia, Dimitrios E. Diamantis, Νικόλαος Παπανδριανός, et al.
Healthcare (2020) Vol. 8, Iss. 4, pp. 493-493
Open Access | Times Cited: 30
Automated detection of skeletal metastasis of lung cancer with bone scans using convolutional nuclear network
Tongtong Li, Qiang Lin, Yanru Guo, et al.
Physics in Medicine and Biology (2021) Vol. 67, Iss. 1, pp. 015004-015004
Open Access | Times Cited: 24
Automated detection of lung cancer-caused metastasis by classifying scintigraphic images using convolutional neural network with residual connection and hybrid attention mechanism
Yanru Guo, Qiang Lin, Shaofang Zhao, et al.
Insights into Imaging (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 16
Machine learning in metastatic cancer research: Potentials, possibilities, and prospects
Olutomilayo Olayemi Petinrin, Faisal Saeed, Muhammad Toseef, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2454-2470
Open Access | Times Cited: 9
Artificial intelligence in skeletal metastasis imaging
Xiying Dong, Guilin Chen, Yuanpeng Zhu, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 23, pp. 157-164
Open Access | Times Cited: 9
The Role of Artificial Intelligence in Advancing Breast Cancer Detection Using Different Imaging Modalities: A Systematic Review
Mohammad Madani, Mohammad Mahdi Behzadi, Sheida Nabavi
(2022)
Open Access | Times Cited: 15
Efficient Machine Learning and Deep Learning Techniques for Detection of Breast Cancer Tumor
Dlshad Abdalrahman Mahmood, Sadegh Abdullah Aminfar
BioMed Target Journal (2024) Vol. 2, Iss. 1, pp. 1-13
Open Access | Times Cited: 2
Page 1 - Next Page

Scroll to top