International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Comparing Results of Classification Techniques Regarding Heart Disease Diagnosing

  • AL badr, Benan Abdullah (College of Science, Department of Computer Science and information, Majmaah University) ;
  • AL ghezzi, Raghad Suliman (College of Science, Department of Computer Science and information, Majmaah University) ;
  • AL moqhem, ALjohara Suliman (College of Science, Department of Computer Science and information, Majmaah University) ;
  • Eljack, Sarah (College of Science, Department of Computer Science and information, Majmaah University)
  • Received : 2022.05.05
  • Published : 2022.05.30
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Abstract

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.

Keywords

Acknowledgement

Great thankful for partnership at scientific research and computer science department and the staff.

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