Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer

Heart diseases are characterized as heterogeneous diseases comprising multiple subtypes. Early diagnosis and prognosis of heart disease are essential to facilitate the clinical management of patients. In this research, a new computational model for predicting early heart disease is proposed. The pre...

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Autores principales:	Abdulaziz Albahr, Marwan Albahar, Mohammed Thanoon, Muhammad Binsawad
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/d63c42a5aa5646a08e6b4affc0bc2394
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spelling	oai:doaj.org-article:d63c42a5aa5646a08e6b4affc0bc23942021-11-22T01:11:03ZComputational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer1687-527310.1155/2021/8628335https://doaj.org/article/d63c42a5aa5646a08e6b4affc0bc23942021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8628335https://doaj.org/toc/1687-5273Heart diseases are characterized as heterogeneous diseases comprising multiple subtypes. Early diagnosis and prognosis of heart disease are essential to facilitate the clinical management of patients. In this research, a new computational model for predicting early heart disease is proposed. The predictive model is embedded in a new regularization based on decaying the weights according to the weight matrices’ standard deviation and comparing the results against its parents (RSD-ANN). The performance of RSD-ANN is far better than that of the existing methods. Based on our experiments, the average validation accuracy computed was 96.30% using either the tenfold cross-validation or holdout method.Abdulaziz AlbahrMarwan AlbaharMohammed ThanoonMuhammad BinsawadHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENComputational Intelligence and Neuroscience, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Abdulaziz Albahr Marwan Albahar Mohammed Thanoon Muhammad Binsawad Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer
description	Heart diseases are characterized as heterogeneous diseases comprising multiple subtypes. Early diagnosis and prognosis of heart disease are essential to facilitate the clinical management of patients. In this research, a new computational model for predicting early heart disease is proposed. The predictive model is embedded in a new regularization based on decaying the weights according to the weight matrices’ standard deviation and comparing the results against its parents (RSD-ANN). The performance of RSD-ANN is far better than that of the existing methods. Based on our experiments, the average validation accuracy computed was 96.30% using either the tenfold cross-validation or holdout method.
format	article
author	Abdulaziz Albahr Marwan Albahar Mohammed Thanoon Muhammad Binsawad
author_facet	Abdulaziz Albahr Marwan Albahar Mohammed Thanoon Muhammad Binsawad
author_sort	Abdulaziz Albahr
title	Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer
title_short	Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer
title_full	Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer
title_fullStr	Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer
title_full_unstemmed	Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer
title_sort	computational learning model for prediction of heart disease using machine learning based on a new regularizer
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/d63c42a5aa5646a08e6b4affc0bc2394
work_keys_str_mv	AT abdulazizalbahr computationallearningmodelforpredictionofheartdiseaseusingmachinelearningbasedonanewregularizer AT marwanalbahar computationallearningmodelforpredictionofheartdiseaseusingmachinelearningbasedonanewregularizer AT mohammedthanoon computationallearningmodelforpredictionofheartdiseaseusingmachinelearningbasedonanewregularizer AT muhammadbinsawad computationallearningmodelforpredictionofheartdiseaseusingmachinelearningbasedonanewregularizer
_version_	1718418370857009152

Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer

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