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Generating geographically and economically realistic large-scale synthetic contact networks: A general method using publicly available data

Autor: Tulchinsky, Alexander Y., Haghpanah, Fardad, Hamilton, Alisa, Kipshidze, Nodar, Klein, Eili Y.

Synthetic contact networks are useful for modeling epidemic spread and social transmission, but data to infer realistic contact patterns that take account of assortative connections at the geographic and economic levels is limited. We developed a met

Externí odkaz: http://arxiv.org/abs/2406.14698

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Zero Inflation as a Missing Data Problem: a Proxy-based Approach

Autor: Phung, Trung, Lee, Jaron J. R., Oladapo-Shittu, Opeyemi, Klein, Eili Y., Gurses, Ayse Pinar, Hannum, Susan M., Weems, Kimberly, Marsteller, Jill A., Cosgrove, Sara E., Keller, Sara C., Shpitser, Ilya

A common type of zero-inflated data has certain true values incorrectly replaced by zeros due to data recording conventions (rare outcomes assumed to be absent) or details of data recording equipment (e.g. artificial zeros in gene expression data). E

Externí odkaz: http://arxiv.org/abs/2406.00549

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Spatial-Temporal Networks for Antibiogram Pattern Prediction

Autor: Fu, Xingbo, Chen, Chen, Dong, Yushun, Vullikanti, Anil, Klein, Eili, Madden, Gregory, Li, Jundong

An antibiogram is a periodic summary of antibiotic resistance results of organisms from infected patients to selected antimicrobial drugs. Antibiograms help clinicians to understand regional resistance rates and select appropriate antibiotics in pres

Externí odkaz: http://arxiv.org/abs/2305.01761

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