A spatially varying change points model for monitoring glaucoma progression using visual field data.
@article{Berchuck2019ASV, title={A spatially varying change points model for monitoring glaucoma progression using visual field data.}, author={Samuel I. Berchuck and Jean-Claude Mwanza and Joshua L. Warren}, journal={Spatial statistics}, year={2019}, volume={30}, pages={ 1-26 } }
2 Citations
Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in Glaucoma.
- Computer Science
- 2019
It is demonstrated that the VAE is a scalable method for analyzing ST data, when the goal is to obtain accurate predictions, as well as a more classical ST method when analyzing longitudinal visual fields from a large cohort of patients in a prospective glaucoma study.
A MULTIVARIATE SPATIOTEMPORAL CHANGE-POINT MODEL OF OPIOID OVERDOSE DEATHS IN OHIO.
- MedicineThe annals of applied statistics
- 2021
A Bayesian multivariate spatiotemporal model is developed for Ohio county overdose death rates from 2007 to 2018 due to different types of opioids to detect county-level shifts in these trends over time for various kinds of opioids.
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