Research Article
Application of Spectral Clustering for the Detection of High Priority Areas of Attention for COVID-19 in Mexico
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@INPROCEEDINGS{10.1007/978-3-030-69839-3_9, author={Rodriguez-Aguilar Roman}, title={Application of Spectral Clustering for the Detection of High Priority Areas of Attention for COVID-19 in Mexico}, proceedings={Computer Science and Health Engineering in Health Services. 4th EAI International Conference, COMPSE 2020, Virtual Event, November 26, 2020, Proceedings}, proceedings_a={COMPSE}, year={2021}, month={7}, keywords={Unsupervised models Spectral cluster COVID-19 Priorization Mexico}, doi={10.1007/978-3-030-69839-3_9} }- Rodriguez-Aguilar Roman
Year: 2021
Application of Spectral Clustering for the Detection of High Priority Areas of Attention for COVID-19 in Mexico
COMPSE
Springer
DOI: 10.1007/978-3-030-69839-3_9
Abstract
The recent COVID-19 pandemic has represented a great challenge for health systems around the world. That is why it is necessary to propose strategies for prioritizing care and containing the pandemic. This work proposes the use of spectral clustering to characterize high-priority areas of care based on key information on the performance of the pandemic as well as health system variables. The result shows the generation of high priority areas not only due to the deaths observed but also due to the clinical, demographic and health system variables.
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