ABSTRACT
INTRODUCTION: Artificial intelligence (AI) has an important role to play in future healthcare offerings. Machine learning and artificial neural networks are subsets of AI that refer to the incorporation of human intelligence into computers to think and behave like humans. OBJECTIVE: The objective of this review article is to discuss perspectives on the AI in relation to Coronavirus disease (COVID-19). METHODS: Google Scholar and PubMed databases were searched to retrieve articles related to COVID-19 and AI. The current evidence is analysed and perspectives on the usefulness of AI in COVID-19 is discussed. RESULTS: The coronavirus pandemic has rendered the entire world immobile, crashing economies, industries, and health care. Telemedicine or tele-dermatology for dermatologists has become one of the most common solutions to tackle this crisis while adhering to social distancing for consultations. While it has not yet achieved its full potential, AI is being used to combat coronavirus disease on multiple fronts. AI has made its impact in predicting disease onset by issuing early warnings and alerts, monitoring, forecasting the spread of disease and supporting therapy. In addition, AI has helped us to build a model of a virtual protein structure and has played a role in teaching as well as social control. CONCLUSION: Full potential of AI is yet to be realized. Expert data collection, analysis, and implementation are needed to improve this advancement.
ABSTRACT
The third outbreak of coronavirus in the form of the COVID-19 infection started in Wuhan, China, in December 2019. The early and rapid spread of this infection across borders can be largely attributed to international air travel that has become a part of modern globalization. In this article, we analyze the spread of the novel coronavirus (SARS-CoV-2) along the routes of international travel, both by air and by sea. Pitfalls of various screening methods used at the airports and the importance of optimal aircraft ventilation are discussed. Also, we suggest measures that can be taken to reduce the risk of transmission associated with air travel.