Application of machine learning methods for predicting the risk of stroke occurrence

Abstract

In the paper, research was carried out in the medical field, which is very important for people and is gaining more and more importance every year. The study was aimed at predicting the occurrence of a stroke, this disease is a serious threat to people's health and lives. To build machine learning models that could solve the problem of predicting the occurrence of a stroke, a very unbalanced dataset was used, which made the work difficult. The best results were shown by the Random Forest model, which reached precision, recall, and f1-score equal to 90%. The obtained results can be useful for doctors and medical workers engaged in the diagnosis and treatment of stroke.