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The term machine learning refers to a collection of tools used for identifying patterns in data. As opposed to traditional methods of pattern identification, machine learning tools relies on artificial intelligence to map out patters from large amounts of data, can self-improve as and when new data becomes available and is quicker in accomplishing these tasks. This review describes various techniques of machine learning that have been used in the past in the prediction, detection and management of infectious diseases, and how these tools are being brought into the battle against COVID-19. In addition, we also discuss their applications in various stages of the pandemic, the advantages, disadvantages and possible pit falls.

Background:Selfie deaths have become an emerging problem and we performed this study to assess the epidemiology of selfie-related deaths across the globe.Subject and Methods:We performed a comprehensive search for keywords such as “selfie deaths; selfie accidents; selfie mortality; self photography deaths; koolfie deaths; mobile death/accidents” from news reports to gather information regarding selfie deaths.Results:From October 2011 to November 2017, there have been 259 deaths while clicking selfies in 137 incidents. The mean age was 22.94 years. About 72.5% of the total deaths occurred in males and 27.5% in females. The highest number of incidents and selfie-deaths has been reported in India followed by Russia, United States, and Pakistan. Drowning, transport, and fall form the topmost reasons for deaths caused by selfies. We also classified reasons for deaths due to selfie as risky behavior or non-risky behavior. Risky behavior caused more deaths and incidents due to selfies than non-risky behavior. The number of deaths in females is less due to risky behavior than non-risky behavior while it is approximately three times in males.Conclusion:“No selfie zones” areas should be declared across tourist areas especially places such as water bodies, mountain peaks, and over tall buildings to decrease the incidence of selfie-related deaths.

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