Back to Search Start Over

Synthetic data & the future of Women's Health: A synergistic relationship.

Authors :
Delanerolle G
Phiri P
Cavalini H
Benfield D
Shetty A
Bouchareb Y
Shi JQ
Zemkoho A
Source :
International journal of medical informatics [Int J Med Inform] 2023 Nov; Vol. 179, pp. 105238. Date of Electronic Publication: 2023 Sep 26.
Publication Year :
2023

Abstract

Objectives: The aim of this perspective is to report the use of synthetic data as a viable method in women's health given the current challenges linked to obtaining life-course data within a short period of time and accessing electronic healthcare data.<br />Methods: We used a 3-point perspective method to report an overview of data science, common applications, and ethical implications.<br />Results: There are several ethical challenges linked to using real-world data, consequently, generating synthetic data provides an alternative method to conduct comprehensive research when used effectively. The use of clinical characteristics to develop synthetic data is a useful method to consider. Aligning this data as closely as possible to the clinical phenotype would enable researchers to provide data that is very similar to that of the real-world.<br />Discussion: Population diversity and disease characterisation is important to optimally use data science. There are several artificial intelligence techniques that can be used to develop synthetic data.<br />Conclusion: Synthetic data demonstrates promise and versatility when used efficiently aligned to clinical problems. Therefore, exploring this option as a viable method in women's health, in particular for epidemiology may be useful.<br />Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: PP has received research grant from Novo Nordisk and Janssen Cilag, and other, educational, other from John Wiley & Sons, outside the submitted work. DB’s work is funded by an EPSRC PhD Studentship with reference number 2612869. AZ is supported by the EPSRC grant EP/V049038/1 and the Alan Turing Institute under the EPSRC grant EP/N510129/1. All other authors report no conflict of interest. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, the Department of Health and Social Care or the Academic institutions.<br /> (Copyright © 2023 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1872-8243
Volume :
179
Database :
MEDLINE
Journal :
International journal of medical informatics
Publication Type :
Academic Journal
Accession number :
37813078
Full Text :
https://doi.org/10.1016/j.ijmedinf.2023.105238