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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Methodol. Mar 20, 2025; 15(1): 98626
Published online Mar 20, 2025. doi: 10.5662/wjm.v15.i1.98626
Published online Mar 20, 2025. doi: 10.5662/wjm.v15.i1.98626
Synthetic data as an investigative tool in hypertension and renal diseases research
Aleena Jamal, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19107, United States
Som Singh, School of Medicine, University of Missouri Kansas City, Kansas, MO 64106, United States
Fawad Qureshi, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN 55905, United States
Author contributions: Jamal A administrated the delegation of the report; Singh S and Jamal A wrote the initial draft; Qureshi F provided critical review and designed the overall concept and outline of the manuscript.
Conflict-of-interest statement: The authors report no conflicts of interest in the creation of this manuscript.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fawad Qureshi, MD, Researcher, Division of Nephrology and Hypertension, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, United States.
Received: July 1, 2024
Revised: August 15, 2024
Accepted: August 29, 2024
Published online: March 20, 2025
Processing time: 90 Days and 3.3 Hours
Revised: August 15, 2024
Accepted: August 29, 2024
Published online: March 20, 2025
Processing time: 90 Days and 3.3 Hours
Core Tip
Core Tip: The application of synthetic data may help accelerate research development as a tool coupled with traditional, established research datasets. However, this tool is still in its early stages in this clinical area. The current literature focuses on three major areas as of current including renal cell carcinoma, chronic kidney disease, and blood pressure and hypertension.