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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:

Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology
Saverio D’Amico, Daniele Dall’Olio, Claudia Sala, et al.
JCO Clinical Cancer Informatics (2023), Iss. 7
Open Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

A Systematic Review of Synthetic Data Generation Techniques Using Generative AI
Mandeep Goyal, Qusay H. Mahmoud
Electronics (2024) Vol. 13, Iss. 17, pp. 3509-3509
Open Access | Times Cited: 28
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence
Jan‐Niklas Eckardt, Waldemar Hahn, Christoph Röllig, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 20
Generative artificial intelligence: synthetic datasets in dentistry
Fahad Umer, Niha Adnan
BDJ Open (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 14
Behavioral health and generative AI: a perspective on future of therapies and patient care
Emre Sezgın, Ian McKay
npj Mental Health Research (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 9
Current Status and Future Directions: The Application of Artificial Intelligence/Machine Learning for Precision Medicine
Kunal Naik, Rahul K. Goyal, Luca Foschini, et al.
Clinical Pharmacology & Therapeutics (2023) Vol. 115, Iss. 4, pp. 673-686
Closed Access | Times Cited: 21
Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?
Andrea Padoan, Janne Cadamuro, Glynis Frans, et al.
Clinical Chemistry and Laboratory Medicine (CCLM) (2024)
Closed Access | Times Cited: 7
Getting real about synthetic data ethics
Danielle Shanley, Joshi Hogenboom, Flora Lysen, et al.
EMBO Reports (2024) Vol. 25, Iss. 5, pp. 2152-2155
Open Access | Times Cited: 6
Artificial intelligence integration in the drug lifecycle and in regulatory science: policy implications, challenges and opportunities
Wahiba Oualikene-Gonin, Marie‐Christine Jaulent, Jean-Pierre Thierry, et al.
Frontiers in Pharmacology (2024) Vol. 15
Open Access | Times Cited: 5
Can We Trust Synthetic Data in Medicine? A Scoping Review of Privacy and Utility Metrics
Bayrem Kaabachi, Jérémie Despraz, Thierry Meurers, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 11
Artificial intelligence for optimizing benefits and minimizing risks of pharmacological therapies: challenges and opportunities
Salvatore Crisafulli, Francesco Ciccimarra, Chiara Bellitto, et al.
Frontiers in Drug Safety and Regulation (2024) Vol. 4
Open Access | Times Cited: 4
Generating Synthetic Medical Dataset Using Generative AI: A Case Study
Partha Pratim Ray
(2025), pp. 259-273
Closed Access
Retrospective Analysis of R-COMP Therapy in Patients with Diffuse Large B-Cell Lymphoma (DLBCL): Assessing the Impact of Sample Selection Bias
Chiara Romano, Francesco Branda, Nicola Petrosillo, et al.
Journal of Clinical Medicine (2025) Vol. 14, Iss. 2, pp. 639-639
Open Access
The Impact of Radiotherapy and Attenuated Chemotherapy Regimens in Older Patients with Classic Hodgkin Lymphoma: A Real-Life Study from the ReLLi Network
Maria Christina Cox, Matteo Caridi, Alexandro Patirelis, et al.
Cancers (2025) Vol. 17, Iss. 5, pp. 765-765
Open Access
Synthetic Data for the Get With The Guidelines–Stroke Registry
Lanjing Wang, Vihaan Manchanda, Holly Picotte, et al.
Journal of the American Heart Association (2025)
Open Access
PARP1 in Melanoma: Mechanistic Insights and Implications for Basic and Clinical Research
Andrea Marranci, Luisa Maresca, Samuele Lodovichi, et al.
Cancer Letters (2025), pp. 217599-217599
Closed Access
The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses
Tuğçe Schmitt, Marie Delnord, Emilie Cauët, et al.
Journal of Health Organization and Management (2025)
Closed Access
A systematic review of privacy-preserving techniques for synthetic tabular health data
Tobias Hyrup, Anton D. Lautrup, Arthur Zimek, et al.
Discover Data (2025) Vol. 3, Iss. 1
Open Access
Human-Centered Artificial Intelligence in Higher Education: A Framework for Systematic Literature Reviews
Thang Le Dinh, Tran Duc Le, Sylvestre Uwizeyemungu, et al.
Information (2025) Vol. 16, Iss. 3, pp. 240-240
Open Access
Synthetic data generation: a privacy-preserving approach to accelerate rare disease research
Jorge M. Mendes, Aziz Barbar, Marwa Refaie
Frontiers in Digital Health (2025) Vol. 7
Open Access
Synthetic tabular data generation in Federated Learning environments: A practical use case for Acute Myeloid Leukemia (Preprint)
Imanol Isasa, Mikel Catalina, Gorka Epelde, et al.
(2025)
Closed Access
Artificial Intelligence in key pricing, reimbursement and market access (PRMA) processes: better, faster, cheaper - can you really pick two?
Eva Susanne Dietrich
Journal of Medical Economics (2025), pp. 1-19
Open Access
Synthetic Data in Healthcare and Drug Development: Definitions, Regulatory Frameworks, Issues
Giuseppe Pasculli, Marco Virgolin, Puja Myles, et al.
CPT Pharmacometrics & Systems Pharmacology (2025)
Open Access
Challenges and Future Perspectives for AI in Hepatology: Breaking Barriers for Better Care
Victoria Kusztos, Douglas A. Simonetto
Journal of Clinical and Experimental Hepatology (2025), pp. 102579-102579
Closed Access
Human-AI Collaboration in Moderating AI-Generated Harmful Content
Sameer Saharan, Mridu Sharma, Meha Khiria, et al.
Advances in computational intelligence and robotics book series (2025), pp. 123-166
Closed Access
Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study
Ippei Akiya, Takuma Ishihara, Keiichi Yamamoto
JMIR Medical Informatics (2024) Vol. 12, pp. e55118-e55118
Open Access | Times Cited: 3
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