Veri madenciliği tekniklerini kullanın enfeksiyon kanıtını belirlemek Irak'ta coronavirus "Covid-19"

As the novel coronavirus pandemic spreads all over the world, countries continue to develop different ways to combat it and limit the spread. As part of the measures taken to combat the virus, information on diagnostic methods, infection symptoms, and the latest research regarding treatment and vaccine has been updated. The main objectives of this research is, to reduce the enormous burden on the healthcare system by providing the best way to diagnose patients and predict the infection of Covid-19 effectively. Moreover, focuses on the most important and demanding medical-appropriate data mining algorithms and aims to explore how data mining can assist physicians in diagnosing Covid-19. Also, to observe a large flow of data through official reports, together with the number of epidemiological and scientific studies in the field of Covid-19. A database was created specifically for (Covid-19) disease, based on one clinical diagnosis sheet organized by the Iraqi Ministry of Health, which is used to detect cases of infection with the virus, (the number of samples was 727). The database included 28 features that were actually associated with the disease to determine the infection because there are many algorithms and data mining tools available, this study considers them only a few tools to evaluate these applications and develop classification rules that can be used for forecasting. Nine algorithms were utilized to determine the most efficient algorithm to build the model. The Random Forest algorithm (RF) received the overall best performance compared to other models in terms of the classification accuracy of 86.30 % to determine the incidence of the virus.