We apply the algorithm to drug overdose data from Indianapolis, showing that the point process defined on the inte- grated data out-performs point processes ...
Oct 12, 2020 · In this work we present a spatial-temporal point process model for drug overdose clustering. ... We apply the algorithm to drug overdose data from ...
We develop a marked point process model for the heterogeneous dataset that uses non-negative matrix factorization to reduce the dimension of the toxicology ...
Sep 7, 2024 · In this work we present a spatial-temporal point process model for drug overdose clustering. ... We apply the algorithm to drug overdose data from ...
Liu, X., Carter, J. A., Ray, B., & Mohler, G. (2021). Point process modeling of drug overdoses with heterogeneous and missing data.
Point Process Modeling of Drug Overdoses with Heterogeneous and Missing Data. Liu, Xueying; Carter, Jeremy; Ray, Brad; Mohler, George. arXiv.org; Ithaca, Oct ...
These models should characterize heterogeneous growth across states using a drug epidemic framework that enables assessments of epidemic onset, rates of growth, ...
NSF Public Access · Search Results · Point process modeling of drug overdoses with heterogeneous and missing data.
Nov 28, 2024 · In the context of the opioid epidemic, Liao et al. introduce the Spatio-TEMporal Mutually Exciting Point Process (STEMMED) model to quantify the ...
In this work we develop a Bayesian multivariate spatiotemporal model for Ohio county overdose death rates from 2007 to 2018 due to different types of opioids.
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