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Comparing Results of Classification Techniques Regarding Heart Disease Diagnosing


Benan Abdullah AL badr, Raghad Suliman AL ghezzi, ALjohara Suliman AL moqhem, Dr.Sarah Eljack .


Vol. 22  No. 5  pp. 135-142


Despite global medical advancements, many patients are misdiagnosed, and more people are dying as a result. We must now develop techniques that provide the most accurate diagnosis of heart disease based on recorded data. To help immediate and accurate diagnose of heart disease, several data mining methods are accustomed to anticipating the disease. A large amount of clinical information offered data mining strategies to uncover the hidden pattern. This paper presents, comparison between different classification techniques, we applied on the same dataset to see what is the best. In the end, we found that the Random Forest algorithm had the best results.


Google Colab, classification technique, Random Forest, Python language, machine learning.