HFC: Towards an Effective Model for the Improvement of heart Diagnosis with Clustering Techniques

Document Type : Original Article


1 Department of Computer Engineering, Aghigh Institute of Higher Education Shahinshahr, Isfahan, Iran

2 Department of Computer Engineering, Al-Rafidain University of Baghdad, Baghdad, Iraq


Heart disease pretends great danger to people, as heart disease has recently become a dangerous disease that acts as a threat to humans. It usually affects all groups from young to old. The biggest challenge in this paper is data pre-processing and discovering a solution to the failure of records Clinical heart, where an effective high-performance model is proposed to enhance heart disease and treat failure in the clinical heart failure records. The current authors applied the techniques of clustering with k-means, expectation-maximization clustering, DBSCAN, support vector clustering, and random clustering herein. Using cluster techniques, we gained good enough results for significantly predicting and improving the performance of heart disease. The goal of the model is a suggestion of a reduction method to find features of heart disease by applying several techniques. Our most important results are to predict faster and better. It indicates that the proposed model is excellent and gives excellent results. This model demonstrated a great superiority over its counterparts through the results obtained in this research. We obtained some values of 130, 980, 183, 125.133, 133, 203, and 125.800. It confirms that this model will predict significantly and improve the performance of the data that we have worked on this.


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    Razieh Asgarnezhad received her B.Sc. and MSc. degrees in Computer Engineering from Kashan Azad University in 2009 and Arak Azad University in 2012, respectively. She received Ph.D. degree from Isfahan Azad University in 2020. Her current researches include Data Mining, Text Mining, Learning Automata, Recommendation System, Sentiment Analysis, and Wireless Sensor Network.

    Karrar Ali Mohsin Alhameedawi received his B.Sc. degrees in Computer Engineering from the Al-Rafidain University of Baghdad in 2018. He received a certified international development trainer specialized in human development from Germany in 2019. After one year, he received the title of the best humanitarian personality in Iraq in 2020. He has experience as a website developer, programmer, the highest educational social networking site in Iraq, and an electronic contest program. He is a member of seven international institutions and has received 200 certificates and a letter of thanks from European and local countries. He is currently an MSc. student at Azad Isfahan University.  His current researches include Data Mining and Big Data.