Giulia Ciaramella
Features selection for SARS-CoV-2 spread in Italy: observation at regional and provincial level.
Rel. Monica Visintin, Guido Pagana. Politecnico di Torino, Master of science program in Ict For Smart Societies, 2020
|
Preview |
PDF (Tesi_di_laurea)
- Thesis
Licence: Creative Commons Attribution Non-commercial No Derivatives. Download (2MB) | Preview |
|
|
Archive (ZIP) (Documenti_allegati)
- Other
Licence: Creative Commons Attribution Non-commercial No Derivatives. Download (427kB) |
Abstract
At the end of 2019 a novel virus -later called SARS-CoV-19- began circulating in the Chinese area of Wuhan, causing a few months later the COVID-19 pandemic. The new disease, which causes severe pneumonia, stirred up problems to the health system of many countries, with hospitals overcrowded with people not receiving the necessary care due to the limited number of respiratory machines. Having spared in the entire globe, the disease captured the attention of all sort of scientists. In the domain of machine learning, researchers applied their knowledge in imaging diagnosis, in therapeutic goal (to study possible usable drugs among some already available on the market), and also in forecasting methods, to know in advance the number of future diseased people.
What is missing in the literature is a study about the possible causes of the virus spread
Relators
Academic year
Publication type
Number of Pages
Course of studies
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modify record (reserved for operators) |
