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The Heart Disease Prediction by Using Random Forest Algorithm
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| Author:
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SADDM HAMDANAHMED, GHAZWAN K. OUDA, WASEEM SAAD NSAIF, MARAM SAAD NSAIF
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| Abstract:
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Healthcare data mainly contains all the patients’ information as well as the parties involved in healthcare industries. The rate storage of such type of data is increased very rapidly. Because of the continuous increasing the size of electronic healthcare data becomes very complex. It becomes very difficult to extract the meaningful information from it by using the traditional methods. Due to advancement in field of statistics, mathematics and every other discipline, now it is possible to extract the meaningful patterns from it and can be used for medical decision making. Data mining is beneficial in such a situation where large collections of healthcare data are available. In this paper we predicted heart disease prediction by using data mining algorithm which is Random Forest. After data classification, the results show 83% accuracy.
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| Keyword:
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Data Mining; WEKA; Decision tree; Random forest Classification; heart disease.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.03.037
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| Download:
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