PREDICTION OF THE OCCURRENCE OF STROKE BASED ON MACHINE LEARNING MODELS
The research conducted in the medical domain addressed a topic of significant importance, steadily growing in relevance each year. The study focused on predicting the onset of strokes, a condition posing a grave risk to individuals' health and lives. Utilizing a highly imbalanced dataset posed a challenge in developing machine learning models capable of effectively predicting stroke occurrences. Among the models examined, the Random Forest model demonstrated the most promising performance, achieving precision, recall, and F1-score metrics of 90%.