Building predictive models for MERS-CoV infections using data mining techniques

ABSTRACT

Background: Recently, the outbreak of MERS-CoV infections caused worldwide attention to Saudi Arabia. The novel virus belongs to the corona viruses family, which is responsible for causing mild to moderate colds. The control and command center of Saudi Ministry of Health issues a daily report on MERS-CoV infection cases. The infection with MERS-CoV can lead to fatal complications, however little information is known about this novel virus. In this paper, we apply two data mining techniques in order to better understand the stability and the possibility of recovery from MERS-CoV infections