Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis
المؤلفون المشاركون
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-09-06
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Background.
Of the machine learning techniques used in predicting coronary heart disease (CHD), neural network (NN) is popularly used to improve performance accuracy.
Objective.
Even though NN-based systems provide meaningful results based on clinical experiments, medical experts are not satisfied with their predictive performances because NN is trained in a “black-box” style.
Method.
We sought to devise an NN-based prediction of CHD risk using feature correlation analysis (NN-FCA) using two stages.
First, the feature selection stage, which makes features acceding to the importance in predicting CHD risk, is ranked, and second, the feature correlation analysis stage, during which one learns about the existence of correlations between feature relations and the data of each NN predictor output, is determined.
Result.
Of the 4146 individuals in the Korean dataset evaluated, 3031 had low CHD risk and 1115 had CHD high risk.
The area under the receiver operating characteristic (ROC) curve of the proposed model (0.749 ± 0.010) was larger than the Framingham risk score (FRS) (0.393 ± 0.010).
Conclusions.
The proposed NN-FCA, which utilizes feature correlation analysis, was found to be better than FRS in terms of CHD risk prediction.
Furthermore, the proposed model resulted in a larger ROC curve and more accurate predictions of CHD risk in the Korean population than the FRS.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Kim, Jae Kwon& Kang, Sanggil. 2017. Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1180872
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Kim, Jae Kwon& Kang, Sanggil. Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis. Journal of Healthcare Engineering No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1180872
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Kim, Jae Kwon& Kang, Sanggil. Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1180872
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1180872
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر