Investigating Role of Supervised Machine Learning Approach in Classification of Diabetic Patient
Investigating Role of Supervised Machine Learning Approach in Classification of Diabetic Patient
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Publisher
Paris: Engineering and Scientific Research Groups
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Language
English
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Publisher
Paris: Engineering and Scientific Research Groups
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Contents
Objectives: Healthcare analytics requires classifying diabetic patient datasets for quicker diagnosis and personalized treatment. This study used SVM, Decision Trees, KNN, ANN, and Logistic Regression to predict type 1 and 2 diabetes. Our detailed performance research shows these algorithms' utility in handling diabetic patient data's complexity. M...
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Full title
Investigating Role of Supervised Machine Learning Approach in Classification of Diabetic Patient
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TN_cdi_proquest_journals_3073676221
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3073676221
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E-ISSN
1112-5209
DOI
10.52783/jes.2987
