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Representing Clinical Conditions on Vital Signs from Healthy Individuals using Latent Modeling

arXiv · AI, language, vision and robotics · article · Sep 14, 2026 · UTC

Machine learning can be crucial to help scale complex signal processing applications in scenarios such as healthcare. However, these machine learning models need rich datasets to be trained and there are often cases where it is not possible to access representative datasets. In this paper, we propose a deep generative model based on conditional variational autoencoders with the objective of augmenting the vital signs of healthy individuals in a way that mimics the patterns of a certain clinical condition. More specifically, we use a publicly available ICU (Intensive Care Unit) dataset to train

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