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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:

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: 31

Showing 1-25 of 31 citing articles:

Diagnosis of skin diseases in the era of deep learning and mobile technology
Evgin Göçeri
Computers in Biology and Medicine (2021) Vol. 134, pp. 104458-104458
Closed Access | Times Cited: 98
Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation
Dimitris Visvikis, Philippe Lambin, Kim Beuschau Mauridsen, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2022) Vol. 49, Iss. 13, pp. 4452-4463
Open Access | Times Cited: 52
Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics
Virginia Liberini, Riccardo Laudicella, Michele Balma, et al.
European Radiology Experimental (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 44
The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer
William Tapper, Gustavo Carneiro, Christos Mikropoulos, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 3, pp. 287-287
Open Access | Times Cited: 13
Emerging Applications of Deep Learning in Bone Tumors: Current Advances and Challenges
Xiaowen Zhou, Hua Wang, Chengyao Feng, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 30
An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM
Νικόλαος Παπανδριανός, Anna Feleki, Serafeim Moustakidis, et al.
Applied Sciences (2022) Vol. 12, Iss. 15, pp. 7592-7592
Open Access | Times Cited: 28
Advances of AI in image-based computer-aided diagnosis: A review
Mst. Nilufa Yeasmin, Md Al Amin, Tasmim Jamal Joti, et al.
Array (2024) Vol. 23, pp. 100357-100357
Open Access | Times Cited: 6
Bone Metastases
Avipsa Hazra, Gowrav Baradwaj, R. Sushma, et al.
(2025), pp. 323-348
Closed Access
Radiomics for Identification and Prediction in Metastatic Prostate Cancer: A Review of Studies
Jake Kendrick, Roslyn J. Francis, Ghulam Mubashar Hassan, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 33
Bone Metastasis in Prostate Cancer: Bone Scan Versus PET Imaging
Nasibeh Mohseninia, Nazanin Zamani-Siahkali, Sara Harsini, et al.
Seminars in Nuclear Medicine (2023) Vol. 54, Iss. 1, pp. 97-118
Open Access | Times Cited: 15
Deep Learning-Based Detection and Classification of Bone Lesions on Staging Computed Tomography in Prostate Cancer: A Development Study
Mason J. Belue, Stephanie A. Harmon, Dong Yang, et al.
Academic Radiology (2024) Vol. 31, Iss. 6, pp. 2424-2433
Closed Access | Times Cited: 4
Artificial Intelligence in Detection, Management, and Prognosis of Bone Metastasis: A Systematic Review
Giuseppe Francesco Papalia, Paolo Brigato, Luisana Sisca, et al.
Cancers (2024) Vol. 16, Iss. 15, pp. 2700-2700
Open Access | Times Cited: 4
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-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
Prediction of Joint Space Narrowing Progression in Knee Osteoarthritis Patients
Charis Ntakolia, Christos Kokkotis, Serafeim Moustakidis, et al.
Diagnostics (2021) Vol. 11, Iss. 2, pp. 285-285
Open Access | Times Cited: 26
Convolutional neural networks for detection of transthyretin amyloidosis in 2D scintigraphy images
Hanna-Leena Halme, Toni Ihalainen, Olli Suomalainen, et al.
EJNMMI Research (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 17
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
Deep Neural Network for Diagnosis of Bone Metastasis
Vincent Peter C. Magboo, Patricia Angela R. Abu
(2022), pp. 144-151
Closed Access | Times Cited: 11
Analysis of Batch Size in the Assessment of Bone Metastasis from Bone Scans in Various Convolutional Neural Networks
Vincent Peter C. Magboo, Patricia Angela R. Abu
Smart innovation, systems and technologies (2023), pp. 221-232
Closed Access | Times Cited: 5
AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review
Νικόλαος Παπανδριανός, Ioannis D. Apostolopoulos, Anna Feleki, et al.
Nuclear Medicine Communications (2022) Vol. 44, Iss. 1, pp. 1-11
Closed Access | Times Cited: 8
MobileLookNet: A Lightweight Convolutional Neural Network for Detection of Osseous Metastasis Using Feature Fusion and Attention Strategies
Irish Danielle Morales, Carlo Joseph Echon, Angelico Ruiz Teaño, et al.
(2024), pp. 1-6
Closed Access | Times Cited: 1
Artificial intelligence and radiomics applied to prostate cancer bone metastasis imaging: A review
S. J. Pawan, Joseph M. Rich, Jonathan Le, et al.
iRadiology (2024)
Open Access | Times Cited: 1
AI‐powered automated analysis of bone scans: A survey
Qiang Lin, Yang He, Sihan Guo
IET Image Processing (2024)
Open Access | Times Cited: 1
Exploring Classification of SPECT MPI images applying convolutional neural networks
Νικόλαος Παπανδριανός, Anna Feleki, Elpiniki I. Papageorgiou
(2021)
Closed Access | Times Cited: 10
Deep learning methods for scientific and industrial research
G.K. Patra, Kantha Rao Bhimala, Ashapurna Marndi, et al.
Handbook of statistics (2023), pp. 107-168
Closed Access | Times Cited: 3
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