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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Association for Computing Machinery
2023
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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 |
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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 |
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57207830966 |
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57207830966 Al-Sideiri A. Cob Z.B.C. Drus S.B.M. |
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Conference Paper |
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Al-Sideiri A. Cob Z.B.C. Drus S.B.M. |
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Al-Sideiri A. Cob Z.B.C. Drus S.B.M. Machine Learning Algorithms for Diabetes Prediction: A Review Paper |
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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 |
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Association for Computing Machinery |
publishDate |
2023 |
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1806427491716300800 |