Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network

The number of factors that can be categorized into the diagnosis of Chronic Kidney Disease (CKD) at an early stage makes information about the diagnosis of the disease divided into information that has many influences and has little influence. This study aims to select diagnoses in medical records w...

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Autores principales:	Noor Chotimah Siti, Warsito Budi, Surarso Bayu
Formato:	article
Lenguaje:	EN FR
Publicado:	EDP Sciences 2021
Materias:	Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/1cb23cf43d044ceca50077b0ede7f295
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spelling	oai:doaj.org-article:1cb23cf43d044ceca50077b0ede7f2952021-11-08T15:19:57ZChronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network2267-124210.1051/e3sconf/202131705030https://doaj.org/article/1cb23cf43d044ceca50077b0ede7f2952021-01-01T00:00:00Zhttps://www.e3s-conferences.org/articles/e3sconf/pdf/2021/93/e3sconf_icenis2021_05030.pdfhttps://doaj.org/toc/2267-1242The number of factors that can be categorized into the diagnosis of Chronic Kidney Disease (CKD) at an early stage makes information about the diagnosis of the disease divided into information that has many influences and has little influence. This study aims to select diagnoses in medical records with the most influential information on chronic kidney disease. The first step is to select a diagnosis with much influence by implementing the Sequential Backward Feature Selection (SBFS). This algorithm eliminates features that are considered to have little influence when compared to other features. In the second step, the features of the best diagnoses are used as input to the Artificial Neural Network (ANN) classification algorithm. The results obtained from this study are information in the form of the best diagnoses that have much influence on chronic kidney disease and the accuracy results based on the selected diagnoses. Based on the study results, 15 features are considered the best of the 18 features used to achieve 88% accuracy results. Compared with conventional methods, this method still requires consideration from the medical staff because it is not a final diagnosis for patients.Noor Chotimah SitiWarsito BudiSurarso BayuEDP SciencesarticleEnvironmental sciencesGE1-350ENFRE3S Web of Conferences, Vol 317, p 05030 (2021)
institution	DOAJ
collection	DOAJ
language	EN FR
topic	Environmental sciences GE1-350
spellingShingle	Environmental sciences GE1-350 Noor Chotimah Siti Warsito Budi Surarso Bayu Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network
description	The number of factors that can be categorized into the diagnosis of Chronic Kidney Disease (CKD) at an early stage makes information about the diagnosis of the disease divided into information that has many influences and has little influence. This study aims to select diagnoses in medical records with the most influential information on chronic kidney disease. The first step is to select a diagnosis with much influence by implementing the Sequential Backward Feature Selection (SBFS). This algorithm eliminates features that are considered to have little influence when compared to other features. In the second step, the features of the best diagnoses are used as input to the Artificial Neural Network (ANN) classification algorithm. The results obtained from this study are information in the form of the best diagnoses that have much influence on chronic kidney disease and the accuracy results based on the selected diagnoses. Based on the study results, 15 features are considered the best of the 18 features used to achieve 88% accuracy results. Compared with conventional methods, this method still requires consideration from the medical staff because it is not a final diagnosis for patients.
format	article
author	Noor Chotimah Siti Warsito Budi Surarso Bayu
author_facet	Noor Chotimah Siti Warsito Budi Surarso Bayu
author_sort	Noor Chotimah Siti
title	Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network
title_short	Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network
title_full	Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network
title_fullStr	Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network
title_full_unstemmed	Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network
title_sort	chronic kidney disease diagnosis system using sequential backward feature selection and artificial neural network
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/1cb23cf43d044ceca50077b0ede7f295
work_keys_str_mv	AT noorchotimahsiti chronickidneydiseasediagnosissystemusingsequentialbackwardfeatureselectionandartificialneuralnetwork AT warsitobudi chronickidneydiseasediagnosissystemusingsequentialbackwardfeatureselectionandartificialneuralnetwork AT surarsobayu chronickidneydiseasediagnosissystemusingsequentialbackwardfeatureselectionandartificialneuralnetwork
_version_	1718441829336088576

Chronic Kidney Disease Diagnosis System using Sequential Backward Feature Selection and Artificial Neural Network

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