id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-19342	Luo, Xiaohui	A Method for Privacy-Safe Synthetic Health Data	2024	6	.pdf	application/pdf	4748	271	52	This type of generated data, which offers both privacy protection and utility, is important for postoperative risk prediction because it ensures data privacy and security, and can be used for academic sharing, providing researchers with a wider range of data resources and promoting collaborative academic research. The experiments in this paper validate the utility of the generated data, statistical similarity between real data and generated data, and the privacy protection of the real data.	cache/ajst-19342.pdf	txt/ajst-19342.txt