Generative modeling of clinical time series via latent stochastic differential equations

Muhammad Aslanimoghanloo

doi:10.1016/j.jbi.2026.105043

Generative modeling of clinical time series via latent stochastic differential equations

2026-04-16

0

PRE

AI

M

Muhammad Aslanimoghanloo *

A

Ahmed ElGazzar

M

Marcel van Gerven

DOI：10.1016/j.jbi.2026.105043

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Abstract

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• Latent SDE: continuous-time stochastic framework for clinical time series modeling. • Naturally handles irregular sampling, partial observations, and multi-modal distributions. • Outperforms existing methods in prediction accuracy and uncertainty quantification.

Keywords:

Latent SDE

clinical time series

stochastic differential equations

irregular sampling

uncertainty quantification

Generative modeling of clinical time series via latent stochastic differential equations

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