文章基本信息

标题：An Integrated Decision Making System for Heart Disease Prediction
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作者：Chiranjeevi M. ; Chandrashekar Hc ; Balaji M S 等
期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2022
卷号：4
期号：4
页码：1279-1281
DOI：10.35629/5252-040410081019
语种：English
出版社：IJAEM JOURNAL
摘要：This top cause of mortality in the world must be diagnosed and treated as soon as possible.. Classification-based decision-making systems have been extensively advocated in numerous research to help forecast cardiac disease. Heart disease may now be predicted more accurately because to the use of an IDMS, or Integrated Decision-Making System. Agglomerative hierarchical clustering, PCA, and Random Forest are all methods for reducing dimensionality. Certain tests demonstrate that the recommended approach outperforms more standard methods when using the Cleveland Heart Disease Dataset (CHDD) from the UCI-ML repository and the Python programming language. Clinicians would benefit from the proposed system of integrated decision-making, which might be useful for future research and projections based on varied databases and critical information about heart disease.
关键词：ML-Machine Learning;DL-Data Mining;AI-Artificial Intelligence;WHO