Identification of Latent Topics in Patients Surviving COVID-19 in Mexico
With the outbreak of the SARS-CoV-2 o COVID19 pandemic, multiple studies of risk factors and their influence on patient deaths have been developed. However, little attention is often paid to analyzing patients in risk groups despite the fact that they have been infected and inpatients can survive. I...
| Authors: | , , , , |
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| Format: | article |
| Publication Date: | 2023 |
| Country: | España |
| Institution: | Universidad Católica San Antonio de Murcia (UCAM) |
| Repository: | RIUCAM. Repositorio Institucional de la Universidad Católica San Antonio de Murcia |
| OAI Identifier: | oai:repositorio.ucam.edu:10952/10770 |
| Online Access: | http://hdl.handle.net/10952/10770 |
| Access Level: | Open access |
| Keyword: | Latent topics Latent Dirichlet Allocation (LDA) COVID-19 Risk factors |
| Summary: | With the outbreak of the SARS-CoV-2 o COVID19 pandemic, multiple studies of risk factors and their influence on patient deaths have been developed. However, little attention is often paid to analyzing patients in risk groups despite the fact that they have been infected and inpatients can survive. In this article, with the dataset available from the Ministery of the health of Mexico, this paper proposes the use of the latent topic extraction algorithm Latent Dirichlet Allocation (LDA) for the study of COVID-19 survival factors in Mexico. The results let us conclude that in the year before strategies for prevention and control of COVID-19, the latent topics support that patients without comorbidities have a low risk of death, compared with the period of 2021, wherein in spite of having some risk factors patients can survive. |
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