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Creating High-Quality Synthetic Health Data: Framework for Model Development and Validation.

Elnaz Karimian SichaniAaron SmithKhaled El EmamLucy Mosquera
Published in: JMIR formative research (2024)
We have presented a generative model for producing synthetic longitudinal health data. The model is formulated by applying the GCP tensor decomposition. We have provided 3 approaches for the synthesis and simulation of a latent factor matrix following the process of factorization. In brief, we have reduced the challenge of synthesizing massive longitudinal health data to synthesizing a nonlongitudinal and significantly smaller data set.
Keyphrases
  • electronic health record
  • public health
  • healthcare
  • big data
  • health information
  • cross sectional
  • health promotion
  • human health
  • risk assessment
  • deep learning