Giuseppe Maria Sechi
Biographic Data
| ID | 7865696 |
|---|---|
| NAME | Giuseppe Maria Sechi |
| GIVEN NAMES | Giuseppe Maria |
| FAMILY NAME | Sechi |
| SIGNATURE | SECHI G M |
| AFFILIATIONS | Agenzia Regionale Emergenza Urgenza |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Neighborhood determinants of vulnerability to heat for cardiovascular health
Generating High-Granularity Covid-19 Territorial Early Alerts Using Emergency Medical Services and Machine Learning
The pandemic of COVID-19 has posed unprecedented threats to healthcare systems worldwide. Great efforts were spent to fight the emergency, with the widespread use of cutting-edge technologies, especially big data analytics and AI. In this context, the present study proposes a novel combination of geographical filtering and machine learning (ML) for the development and optimization of a COVID-19 early alert system based on Emergency Medical Servic…
Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of Covid-19 Diffusion in the Lombardy Region (Italy)
this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH 3 . As NH 3 could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated
Mapping Spatiotemporal Diffusion of Covid-19 in Lombardy (Italy) on the Base of Emergency Medical Services Activities
The epidemic of coronavirus-disease-2019 (COVID-19) started in Italy with the first official diagnosis on 21 February 2020; However, it is not known how many cases were already present in earlier days and weeks, thus limiting the possibilities of conducting any retrospective analysis. We hypothesized that an unbiased representation of COVID-19 diffusion in these early phases could be inferred by the georeferenced calls to the emergency number rel…
No prominent works on this page.
Mapping Spatiotemporal Diffusion of Covid-19 in Lombardy (Italy) on the Base of Emergency Medical Services Activities
The epidemic of coronavirus-disease-2019 (COVID-19) started in Italy with the first official diagnosis on 21 February 2020; However, it is not known how many cases were already present in earlier days and weeks, thus limiting the possibilities of conducting any retrospective analysis. We hypothesized that an unbiased representation of COVID-19 diffusion in these early phases could be inferred by the georeferenced calls to the emergency number rel…
Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of Covid-19 Diffusion in the Lombardy Region (Italy)
this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH 3 . As NH 3 could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated
Generating High-Granularity Covid-19 Territorial Early Alerts Using Emergency Medical Services and Machine Learning
The pandemic of COVID-19 has posed unprecedented threats to healthcare systems worldwide. Great efforts were spent to fight the emergency, with the widespread use of cutting-edge technologies, especially big data analytics and AI. In this context, the present study proposes a novel combination of geographical filtering and machine learning (ML) for the development and optimization of a COVID-19 early alert system based on Emergency Medical Servic…
Neighborhood determinants of vulnerability to heat for cardiovascular health
Geography (4 works) · Medicine (4 works) · COVID-19 epidemiological studies (3 works) · Cartography (2 works) · Computer security (2 works) · Coronavirus disease 2019 (COVID-19 (2 works) · Data-Driven Disease Surveillance (2 works) · Disease (2 works) · Environmental health (2 works) · Medical emergency (2 works)