[HTML][HTML] An evaluation of the replicability of analyses using synthetic health data
Synthetic data generation is being increasingly used as a privacy preserving approach for
sharing health data. In addition to protecting privacy, it is important to ensure that generated …
sharing health data. In addition to protecting privacy, it is important to ensure that generated …
Assessing privacy and quality of synthetic health data
This paper builds on the results of the ESANN 2019 conference paper" Privacy Preserving
Synthetic Health Data"[16], which develops metrics for assessing privacy and utility of …
Synthetic Health Data"[16], which develops metrics for assessing privacy and utility of …
A primer on synthetic health data
JA Bartell, SB Valentin, A Krogh, H Langberg… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advances in deep generative models have greatly expanded the potential to create
realistic synthetic health datasets. These synthetic datasets aim to preserve the …
realistic synthetic health datasets. These synthetic datasets aim to preserve the …
[HTML][HTML] Fake it till you make it: Guidelines for effective synthetic data generation
Synthetic data provides a privacy protecting mechanism for the broad usage and sharing of
healthcare data for secondary purposes. It is considered a safe approach for the sharing of …
healthcare data for secondary purposes. It is considered a safe approach for the sharing of …
[HTML][HTML] A multifaceted benchmarking of synthetic electronic health record generation models
Synthetic health data have the potential to mitigate privacy concerns in supporting
biomedical research and healthcare applications. Modern approaches for data generation …
biomedical research and healthcare applications. Modern approaches for data generation …
Generation and evaluation of privacy preserving synthetic health data
We develop metrics for measuring the quality of synthetic health data for both education and
research. We use novel and existing metrics to capture a synthetic dataset's resemblance …
research. We use novel and existing metrics to capture a synthetic dataset's resemblance …
[HTML][HTML] Evaluating identity disclosure risk in fully synthetic health data: model development and validation
K El Emam, L Mosquera, J Bass - Journal of medical Internet research, 2020 - jmir.org
Background There has been growing interest in data synthesis for enabling the sharing of
data for secondary analysis; however, there is a need for a comprehensive privacy risk …
data for secondary analysis; however, there is a need for a comprehensive privacy risk …
Synthetic data generation: State of the art in health care domain
Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …
research in every aspect of life including the health care domain. However, privacy risks and …
Fidelity and privacy of synthetic medical data
O Mendelevitch, MD Lesh - arXiv preprint arXiv:2101.08658, 2021 - arxiv.org
The digitization of medical records ushered in a new era of big data to clinical science, and
with it the possibility that data could be shared, to multiply insights beyond what investigators …
with it the possibility that data could be shared, to multiply insights beyond what investigators …
[HTML][HTML] Generation and evaluation of synthetic patient data
Background Machine learning (ML) has made a significant impact in medicine and cancer
research; however, its impact in these areas has been undeniably slower and more limited …
research; however, its impact in these areas has been undeniably slower and more limited …