Predictive analysis in determining the dissemination of infectious disease and its severity
| Autor: | E. Gothai, K Srinithy, R. R. Rajalaxmi, P. Natesan, T Vignesh Balaji, T Vignesh |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
education.field_of_study Computer science Population Yellow fever Outbreak medicine.disease Cholera Dengue fever 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Infectious disease (medical specialty) Environmental health medicine Chicken Pox education 030217 neurology & neurosurgery Malaria |
| Zdroj: | 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). |
| Popis: | Epidemic diseases are the contagious diseases that have the power to unfold into the entire nation if its contagion measuring had reached the level of an outbreak and also manage to wipe out the majority of the population. There are some common and well-known epidemic disease outbreaks that were happened in the entire world such as malaria, dengue, swine flu, yellow fever, chicken pox, cholera, diphtheria, bird flu, influenza, and many more. Infectious disease surveillance is one of the most comprehensive processes during which information or data on such infectious disease disseminations, vectors and outbreaks are collected, analyzed, and interpreted in a consistent and systematic manner. Moreover, the outcomes and results ought to be distributed to people in a rapid way so as to have command and control over preventing infectious disease. Subsequently, to handle situations in real time, it is significant and important to create an infectious disease prediction model. The ultimate aim is to create a model using LSTM (Long Short Term Memory) wherein the predictive analysis is demonstrated to be effective in figuring out the epidemic disease infected location and its severity. |
| Databáze: | OpenAIRE |
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