Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications
<p>The recent availability of electronic health records (EHRs) have provided enormous opportunities to develop artificial intelligence (AI) algorithms. However, patient privacy has become a major concern that limits data sharing across hospital settings and subsequently hinders the advances in...
Autori principali: | Li, J, Cairns, BJ, Zhu, T |
---|---|
Natura: | Journal article |
Lingua: | English |
Pubblicazione: |
Springer Nature
2023
|
Documenti analoghi
Documenti analoghi
-
Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications
di: Jin Li, et al.
Pubblicazione: (2023-05-01) -
On the evaluation of synthetic longitudinal electronic health records
di: Jim L. Achterberg, et al.
Pubblicazione: (2024-08-01) -
Generative artificial intelligence: synthetic datasets in dentistry
di: Fahad Umer, et al.
Pubblicazione: (2024-03-01) -
Synthetic electronic health records generated with variational graph autoencoders
di: Giannis Nikolentzos, et al.
Pubblicazione: (2023-04-01) -
A Multifaceted benchmarking of synthetic electronic health record generation models
di: Chao Yan, et al.
Pubblicazione: (2022-12-01)