Synthetic data in medicine: generation, evaluation and limits

被引：0
|
作者：
Benani, Alaedine [1 ,2 ]
Vibert, Julien [3 ]
Demuth, Stanislas [4 ,5 ]
机构：
[1] Univ Paris Cite, Hop Europeen Georges Pompidou HEGP, AP HP, Serv Med Vasc, Paris, France
[2] Zoi, Paris, France
[3] Gustave Roussy, Dept Innovat Therapeut & Essais Prec DITEP, Inserm, U981, Paris, France
[4] Nantes Univ, CR2TI Ctr Rech Transplantat & Immunol Translat, Inserm, U1064, Nantes, France
[5] Ctr Hosp Strasbourg, Ctr Invest Clin, Inserm, CIC 1434, Strasbourg, France
来源：
M S-MEDECINE SCIENCES | 2024年 / 40卷 / 8-9期
关键词：
D O I：
10.1051/medsci/2024091
中图分类号：
R-3 [医学研究方法]; R3 [基础医学];
学科分类号：
1001 ;
摘要：
Recent technological advances in data science hold great promise in medicine. Large-sized high-quality datasets are essential but often difficult to obtain due to privacy, cost, and practical challenges. Here, we discuss synthetic data's generation, evaluation, and regulation, highlighting its current applications and limits.
引用
收藏
页码：661 / 664
页数：4
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