Cluster-based analysis of infectious disease occurrences using tensor decomposition: a case study of South Korea
For a long time, various epidemics, such as lower respiratory infections and diarrheal
diseases, have caused serious social losses and costs. Various methods for analyzing …
diseases, have caused serious social losses and costs. Various methods for analyzing …
Hot-spots detection in count data by Poisson assisted smooth sparse tensor decomposition
Count data occur widely in many bio-surveillance and healthcare applications, eg the
numbers of new patients of different types of infectious diseases from different …
numbers of new patients of different types of infectious diseases from different …
Tensor decomposition for infectious disease incidence data
H Korevaar, CJ Metcalf… - Methods in ecology and …, 2020 - Wiley Online Library
Many demographic and ecological processes generate seasonal and other periodicities.
Seasonality in infectious disease transmission can result from climatic forces such as …
Seasonality in infectious disease transmission can result from climatic forces such as …
Data distribution and tensor influence analysis of different clustering methods
H Zhang, H Ye, D Shi, Z Xue, W Fan, F Meng - 2023 - researchsquare.com
At present, people are in the era of big data, which is changing people's views of the world.
However, it has the characteristics of various types, huge scale, and complex relationships …
However, it has the characteristics of various types, huge scale, and complex relationships …
Characterizing and discovering spatiotemporal social contact patterns for healthcare
During an epidemic, the spatial, temporal and demographic patterns of disease transmission
are determined by multiple factors. In addition to the physiological properties of the …
are determined by multiple factors. In addition to the physiological properties of the …
Rapid detection of hot-spot by tensor decomposition with application to weekly gonorrhea data
In many bio-surveillance and healthcare applications, data sources are measured from
many spatial locations repeatedly over time, say, daily/weekly/monthly. In these applications …
many spatial locations repeatedly over time, say, daily/weekly/monthly. In these applications …
Multi-faceted analysis and prediction for the outbreak of pediatric respiratory syncytial virus
Objectives Respiratory syncytial virus (RSV) is a significant cause of pediatric
hospitalizations. This article aims to utilize multisource data and leverage the tensor …
hospitalizations. This article aims to utilize multisource data and leverage the tensor …
Detection of space–time clusters using a topological hierarchy for geospatial data on COVID-19 in Japan
Y Takemura, F Ishioka, K Kurihara - … Journal of Statistics and Data Science, 2022 - Springer
In this paper, we detected space–time clusters using data on coronavirus disease 2019
(COVID-19) collected daily by each prefecture in Japan. COVID-19 has spread globally …
(COVID-19) collected daily by each prefecture in Japan. COVID-19 has spread globally …
Rapid detection of hot-spot by tensor decomposition on space and circular time with application to weekly gonorrhea data
In many bio-surveillance and healthcare applications, data sources are measured from
many spatial locations repeatedly over time, say, daily/weekly/monthly. In these applications …
many spatial locations repeatedly over time, say, daily/weekly/monthly. In these applications …
A tensor decomposition model for longitudinal microbiome studies
A tensor decomposition model for longitudinal microbiome studies Page 1 The Annals of
Applied Statistics 2023, Vol. 17, No. 2, 1105–1126 https://doi.org/10.1214/22-AOAS1661 © …
Applied Statistics 2023, Vol. 17, No. 2, 1105–1126 https://doi.org/10.1214/22-AOAS1661 © …