Synthetic data generation methods in healthcare: A review on open-source tools and methods
University of Ioannina · National Technical University of Athens
Abstract
Synthetic data generation has emerged as a promising solution to overcome the challenges which are posed by data scarcity and privacy concerns, as well as, to address the need for training artificial intelligence (AI) algorithms on unbiased data with sufficient sample size and statistical power. Our review explores the application and efficacy of synthetic data methods in healthcare considering the diversity of medical data. To this end, we systematically searched the PubMed and Scopus databases with a great focus on tabular, imaging, radiomics, time-series, and omics data. Studies involving multi-modal synthetic data generation were also explored. The type of method used for the synthetic data generation…
Citation impact
- FWCI
- 60.57
- Percentile
- 100%
- References
- 124
Authors
7Topics & keywords
- Computer science
- Python (programming language)
- Artificial intelligence
- Data science
- Synthetic data
- Machine learning
- Big data
- Data mining