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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:

Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development
Tyler Bradshaw, Ronald Boellaard, Joyita Dutta, et al.
Journal of Nuclear Medicine (2021) Vol. 63, Iss. 4, pp. 500-510
Open Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Joint EANM/SNMMI guideline on radiomics in nuclear medicine
Mathieu Hatt, Aron K. Krizsan, Arman Rahmim, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2022) Vol. 50, Iss. 2, pp. 352-375
Open Access | Times Cited: 79
A Guide to Cross-Validation for Artificial Intelligence in Medical Imaging
Tyler Bradshaw, Zachary Huemann, Junjie Hu, et al.
Radiology Artificial Intelligence (2023) Vol. 5, Iss. 4
Open Access | Times Cited: 63
TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images — a multi-center generalizability analysis
Fereshteh Yousefirizi, Ivan S. Klyuzhin, Joo Hyun O, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2024) Vol. 51, Iss. 7, pp. 1937-1954
Closed Access | Times Cited: 21
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Alejandro F. Frangi, Antonio R. Porras, et al.
BMJ (2025), pp. e081554-e081554
Open Access | Times Cited: 9
Optimizing Cancer Treatment: Exploring the Role of AI in Radioimmunotherapy
Hossein Azadinejad, Mohammad Farhadi Rad, Ahmad Shariftabrizi, et al.
Diagnostics (2025) Vol. 15, Iss. 3, pp. 397-397
Open Access | Times Cited: 2
Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines)
Abhinav K. Jha, Tyler Bradshaw, Irène Buvat, et al.
Journal of Nuclear Medicine (2022) Vol. 63, Iss. 9, pp. 1288-1299
Open Access | Times Cited: 61
[18F]FDG-PET/CT Radiomics and Artificial Intelligence in Lung Cancer: Technical Aspects and Potential Clinical Applications
Reyhaneh Manafi‐Farid, Emran Askari, Isaac Shiri, et al.
Seminars in Nuclear Medicine (2022) Vol. 52, Iss. 6, pp. 759-780
Open Access | Times Cited: 54
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: 54
18F-FDG PET Maximum-Intensity Projections and Artificial Intelligence: A Win-Win Combination to Easily Measure Prognostic Biomarkers in DLBCL Patients
Kibrom Berihu Girum, Louis Rebaud, Anne‐Ségolène Cottereau, et al.
Journal of Nuclear Medicine (2022) Vol. 63, Iss. 12, pp. 1925-1932
Open Access | Times Cited: 38
Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens
Elmira Yazdani, Parham Geramifar, Najme Karamzade-Ziarati, et al.
Diagnostics (2024) Vol. 14, Iss. 2, pp. 181-181
Open Access | Times Cited: 14
Recent advances and impending challenges for the radiopharmaceutical sciences in oncology
Suzanne E. Lapi, Peter J. H. Scott, Andrew M. Scott, et al.
The Lancet Oncology (2024) Vol. 25, Iss. 6, pp. e236-e249
Closed Access | Times Cited: 13
Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept
Morteza Salehjahromi, Tatiana V. Karpinets, Sheeba J. Sujit, et al.
Cell Reports Medicine (2024) Vol. 5, Iss. 3, pp. 101463-101463
Open Access | Times Cited: 8
Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem
Babak Saboury, Tyler Bradshaw, Ronald Boellaard, et al.
Journal of Nuclear Medicine (2022) Vol. 64, Iss. 2, pp. 188-196
Open Access | Times Cited: 35
Pix2Pix generative adversarial network for low dose myocardial perfusion SPECT denoising
Jingzhang Sun, Yu Du, Chien‐Ying Li, et al.
Quantitative Imaging in Medicine and Surgery (2022) Vol. 12, Iss. 7, pp. 3539-3555
Open Access | Times Cited: 34
Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging
Robert J.H. Miller, Keiichiro Kuronuma, Ananya Singh, et al.
Journal of Nuclear Medicine (2022), pp. jnumed.121.263686-jnumed.121.263686
Open Access | Times Cited: 28
Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance
Jonathan Herington, Melissa D. McCradden, Kathleen Creel, et al.
Journal of Nuclear Medicine (2023) Vol. 64, Iss. 10, pp. 1509-1515
Open Access | Times Cited: 20
Generative Adversarial Networks for Anomaly Detection in Biomedical Imaging: A Study on Seven Medical Image Datasets
Marzieh Esmaeili, Amirhosein Toosi, Arash Roshanpoor, et al.
IEEE Access (2023) Vol. 11, pp. 17906-17921
Open Access | Times Cited: 19
Current state and prospects of artificial intelligence in allergy
Merlijn van Breugel, Rudolf S.N. Fehrmann, Marnix Bügel, et al.
Allergy (2023) Vol. 78, Iss. 10, pp. 2623-2643
Open Access | Times Cited: 19
Evaluating Outcome Prediction via Baseline, End-of-Treatment, and Delta Radiomics on PET-CT Images of Primary Mediastinal Large B-Cell Lymphoma
Fereshteh Yousefirizi, Claire Gowdy, Ivan S. Klyuzhin, et al.
Cancers (2024) Vol. 16, Iss. 6, pp. 1090-1090
Open Access | Times Cited: 7
Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT–SEQUOIA
Gijs D. van Praagh, P. H. Nienhuis, Melanie Reijrink, et al.
Medical Physics (2024) Vol. 51, Iss. 6, pp. 4297-4310
Open Access | Times Cited: 6
Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics
Pegah Moradi Khaniabadi, Yassine Bouchareb, Humoud Al-Dhuhli, et al.
Computers in Biology and Medicine (2022) Vol. 150, pp. 106165-106165
Open Access | Times Cited: 27
Quantitative PET-based biomarkers in lymphoma: getting ready for primetime
Juan Pablo Alderuccio, Russ Kuker, Fei Yang, et al.
Nature Reviews Clinical Oncology (2023) Vol. 20, Iss. 9, pp. 640-657
Closed Access | Times Cited: 16
Role of Artificial Intelligence in PET/CT Imaging for Management of Lymphoma
Eren M. Veziroglu, Faraz Farhadi, Navid Hasani, et al.
Seminars in Nuclear Medicine (2023) Vol. 53, Iss. 3, pp. 426-448
Closed Access | Times Cited: 15
Regulatory considerations for medical imaging AI/ML devices in the United States: concepts and challenges
Nicholas Petrick, Weijie Chen, Jana G. Delfino, et al.
Journal of Medical Imaging (2023) Vol. 10, Iss. 05
Open Access | Times Cited: 13
Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation
Jonathan Herington, Melissa D. McCradden, Kathleen Creel, et al.
Journal of Nuclear Medicine (2023) Vol. 64, Iss. 12, pp. 1848-1854
Open Access | Times Cited: 13
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