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A Feature-Driven Decision Support System for Heart Failure Prediction Based on χ2 Statistical Model and Gaussian Naive Bayes
المؤلفون المشاركون
Khan, Shafqat Ullah
Ali, Liaqat
Golilarz, Noorbakhsh Amiri
Yakubu, Imrana
Qasim, Iqbal
Noor, Adeeb
Nour, Redhwan
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-11-20
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Heart failure (HF) is considered a deadliest disease worldwide.
Therefore, different intelligent medical decision support systems have been widely proposed for detection of HF in literature.
However, low rate of accuracies achieved on the HF data is a major problem in these decision support systems.
To improve the prediction accuracy, we have developed a feature-driven decision support system consisting of two main stages.
In the first stage, χ2 statistical model is used to rank the commonly used 13 HF features.
Based on the χ2 test score, an optimal subset of features is searched using forward best-first search strategy.
In the second stage, Gaussian Naive Bayes (GNB) classifier is used as a predictive model.
The performance of the newly proposed method (χ2-GNB) is evaluated by using an online heart disease database of 297 subjects.
Experimental results show that our proposed method could achieve a prediction accuracy of 93.33%.
The developed method (i.e., χ2-GNB) improves the HF prediction performance of GNB model by 3.33%.
Moreover, the newly proposed method also shows better performance than the available methods in literature that achieved accuracies in the range of 57.85–92.22%.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ali, Liaqat& Khan, Shafqat Ullah& Golilarz, Noorbakhsh Amiri& Yakubu, Imrana& Qasim, Iqbal& Noor, Adeeb…[et al.]. 2019. A Feature-Driven Decision Support System for Heart Failure Prediction Based on χ2 Statistical Model and Gaussian Naive Bayes. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1130631
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ali, Liaqat…[et al.]. A Feature-Driven Decision Support System for Heart Failure Prediction Based on χ2 Statistical Model and Gaussian Naive Bayes. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1130631
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ali, Liaqat& Khan, Shafqat Ullah& Golilarz, Noorbakhsh Amiri& Yakubu, Imrana& Qasim, Iqbal& Noor, Adeeb…[et al.]. A Feature-Driven Decision Support System for Heart Failure Prediction Based on χ2 Statistical Model and Gaussian Naive Bayes. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1130631
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130631
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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