A two-stage variational autoencoder with per-latent-dimension linear regression predicts future glaucoma visual fields more accurately than a classical patient-level spatiotemporal model, especially with few baseline visits.
I., Mukherjee, S., Medeiros, F
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Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in Glaucoma
A two-stage variational autoencoder with per-latent-dimension linear regression predicts future glaucoma visual fields more accurately than a classical patient-level spatiotemporal model, especially with few baseline visits.