The Data Mining (Concepts, Algorithms) and Its Application to predict and Control Covid-19 Epidemic

Abstract

In recent years, the issue of data mining has been considered by researchers due to the widespread access to large amount of data, the urgent need for information, proper, fast and accurate identification and diagnosis of various topics. Data mining discovers valid, fresh and useful patterns of available data which can provide valuable analytics for very large data sets. Today, the scope of its use has expanded and various data mining algorithms are used to identify and predict important issues in the field of health. The health sector is in the greatest need for data mining. The move from traditional medicine to evidence-based medicine is one of the things that can confirm this. In today's world, Covid-19 quickly hit other countries in addition to China like a hurricane, killing many people around the world. Due to the large amount of data in the field of medicine, the data mining process has played a very effective role in the management of various diseases such as prognosis, diagnosis and treatment. The main purpose of using data mining algorithms in medical sciences is to make better use of databases and discover hidden knowledge in order to help physicians make better decisions. The present article, which is prepared in a review manner using internet and library resources, tries to examine the concepts, data mining algorithms and their application in the field of health, especially to help diagnosing Covid-19. Finally, practical suggestions are provided.