Dr. Seyed Mohammad Ayyoubzadeh Wins Best Paper Award at the 22nd Ibn Sina Festival, Tehran University of Medical Sciences
Dr. Seyed Mohammad Ayyoubzadeh was awarded the Best Paper Award at the 22nd Ibn Sina Festival of Tehran University of Medical Sciences
According to the Public Relations Office of Tehran University of Medical Sciences, School of Allied Medical Sciences, Dr. Ayyoubzadeh was recognized for his outstanding research paper. In an interview with the Public Relations Office of the School of Allied Medical Sciences, Dr. Ayyoubzadeh explained that the idea for the research came from his personal experience of searching for hand sanitizers during the early days of the COVID-19 pandemic. He wondered if internet search trends could be used to predict the spread of the virus. By extracting data on search trends for hand sanitizers from Google Trends and COVID-19 cases from Worldometer, he found a correlation between the two. Based on this correlation, he and his colleagues developed two artificial intelligence models to predict COVID-19 cases in Iran. The title of the paper is "Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study". This study aimed to predict the incidence of COVID-19 in Iran. The recent COVID-19 pandemic has had a significant impact on the world. Iran is one of the ten countries that has been most affected by this pandemic. Search engines provide valuable data from the population, and this data can be used for analysis and epidemic analysis. The use of artificial intelligence and data mining methods on these data sources can provide a better view of the COVID-19 pandemic to manage the health crisis at the national and global levels. According to the results of this study, data mining and artificial intelligence methods can be used to predict epidemics. These predictions can be used to monitor healthcare for planning, policymaking, and allocating healthcare resources.
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