Research on Heart Attack Reported by Researchers at Northern Border University (Comparative Analysis of Machine Learning Algorithms for Investigating Myocardial Infarction Complications).

Researchers at Northern Border University have conducted a study comparing machine learning algorithms for investigating complications related to myocardial infarction (heart attack). The study aimed to classify these complications and predict fatal outcomes. The algorithms tested were Multilayer Perceptron (MLP), Naive Bayes (NB), and Decision Tree (DT). The results showed that the MLP classifier performed best with the full dataset, while the DT classifier was more favorable when the dataset size was reduced using an attribute selection algorithm. This research provides valuable insights into the use of machine learning in understanding and predicting myocardial infarction complications. [Extracted from the article]