Author: Aboul Ella Hassanien; Lamia Nabil Mahdy; Kadry Ali Ezzat; Haytham H. Elmousalami; Hassan Aboul Ella
Title: Automatic X-ray COVID-19 Lung Image Classification System based on Multi-Level Thresholding and Support Vector Machine Document date: 2020_4_6
ID: 45dpoepu_2
Snippet: By comparison, SARS killed 774 people in 2003 mostly in China, the epicenter of the pandemic outbreak. COVID-19 and SARS are spread across continents, infecting animals and humans, and using similar mechanisms to enter and injure the cell. On the front line, the tactical response to COVID-19 is similar to that of the SARS 2003 outbreak however, there is one major difference, the COVID-19 emergency is occurring in a much more digitized and connect.....
Document: By comparison, SARS killed 774 people in 2003 mostly in China, the epicenter of the pandemic outbreak. COVID-19 and SARS are spread across continents, infecting animals and humans, and using similar mechanisms to enter and injure the cell. On the front line, the tactical response to COVID-19 is similar to that of the SARS 2003 outbreak however, there is one major difference, the COVID-19 emergency is occurring in a much more digitized and connected to our world. The amount of data produced from the dawn of humankind through 2003 is generated today within a few minutes. Furthermore, advanced intelligence models, such as those based on artificial intelligence (AI) and machine learning (ML), have shown great potential in tracing the source or predicting the future spread of infectious diseases. It is therefore imperative to leverage big data and intelligent analytics and put them to good use for public health.
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