A5039842969- COVID-19 epidemiological studies
- Influenza Virus Research Studies
- Viral Infections and Vectors
- Data-Driven Disease Surveillance
Army Medical University
2022-2024
Abstract Background Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous for predicting diseases, and they exhibited varying degrees success. However, there a lack prediction benchmarks that integrate linear nonlinear effectively use internet data. The aim this paper is develop model rate diseases integrates multiple multisource data, realizing ground-breaking research. Results disease dataset from an official release includes...
With the recent prevalence of COVID-19, cryptic transmission is worthy attention and research. Early perception occurrence development risk an important part controlling spread COVID-19. Previous relevant studies have limited data sources, no effective analysis has been carried out on transmission. Hence, we collect Internet multisource big (including retrieval, migration, media data) propose comprehensive relative application strategies to eliminate impact national data. We use statistical...