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Machine Learning Algorithms for Diabetes Prediction: A Review Paper

Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine alg...

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Main Authors: Al-Sideiri A., Cob Z.B.C., Drus S.B.M.
Other Authors: 57207830966
Format: Conference Paper
Published: Association for Computing Machinery 2023
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id my.uniten.dspace-24242
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spelling my.uniten.dspace-242422023-05-29T15:22:24Z Machine Learning Algorithms for Diabetes Prediction: A Review Paper Al-Sideiri A. Cob Z.B.C. Drus S.B.M. 57207830966 25824919900 56330463900 Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms The early diagnosis of the diabetes disease is a very important for cure process, and that provides an ease process of treatment for both the patient and the doctor. At this point, statistical methods and data mining algorithms can provide significance chances for early diagnosis of diabetes mellitus (DM). In the literature, many studies have been published for solution of this problem. Initially, these studies are analyzed in detail and classified according to their methodologies. The main aim of this paper is to provide the comprehensive and detailed review of the diagnosis of diabetes by machine learning algorithms. Also, this paper presents a literature review on the diagnosis diabetes up to the mid of 2019. This paper provides to guide future research and knowledge accumulation and creation of classification and prediction techniques in diagnosis of diabetes. This study shows that the Support Vector Machine (SVM) algorithm is the most used machine learning algorithms and it provide more accurate and powerful results. � 2019 ACM. Final 2023-05-29T07:22:24Z 2023-05-29T07:22:24Z 2019 Conference Paper 10.1145/3388218.3388231 2-s2.0-85086183023 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086183023&doi=10.1145%2f3388218.3388231&partnerID=40&md5=8bb6d9318ec1871f72e6cb95610c189e https://irepository.uniten.edu.my/handle/123456789/24242 27 32 Association for Computing Machinery Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms
author2 57207830966
author_facet 57207830966
Al-Sideiri A.
Cob Z.B.C.
Drus S.B.M.
format Conference Paper
author Al-Sideiri A.
Cob Z.B.C.
Drus S.B.M.
spellingShingle Al-Sideiri A.
Cob Z.B.C.
Drus S.B.M.
Machine Learning Algorithms for Diabetes Prediction: A Review Paper
author_sort Al-Sideiri A.
title Machine Learning Algorithms for Diabetes Prediction: A Review Paper
title_short Machine Learning Algorithms for Diabetes Prediction: A Review Paper
title_full Machine Learning Algorithms for Diabetes Prediction: A Review Paper
title_fullStr Machine Learning Algorithms for Diabetes Prediction: A Review Paper
title_full_unstemmed Machine Learning Algorithms for Diabetes Prediction: A Review Paper
title_sort machine learning algorithms for diabetes prediction: a review paper
publisher Association for Computing Machinery
publishDate 2023
_version_ 1806427491716300800
score 13.211869

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