Diabetes Prediction Using Novel Machine Learning Methods

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Author(s): Sagar Saikia (National Institute of Technology, Meghalaya, India), Jonti Deuri (Assam Don Bosco University, India), Riya Deka (NERIM Group of Institutions, India)and Rituparna Nath (NERIM Group of Institutions, India)
Copyright: 2024
Pages: 20
Source title: Critical Approaches to Data Engineering Systems and Analysis
Source Author(s)/Editor(s): Abhijit Bora (Assam Don Bosco University, India), Papul Changmai (Assam Don Bosco University, India)and Mrutyunjay Maharana (Xi’an Jiatong University, China)
DOI: 10.4018/979-8-3693-2260-4.ch008

Keywords: Computer Engineering / Data Warehousing / Engineering Science Reference / Library & Information Science

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Abstract

Diabetes is a prevalent and chronic health condition affecting millions globally. Diabetes is caused by a combination of many factors including obesity, excessive blood glucose levels, abnormal cholesterol levels, family history, physical inactivity, bad food habits, and other causes. Frequent urination, increased thirst, increased hunger, and loss of weight are the common symptoms of diabetes. A person having diabetes has heavy risks of heart disease, kidney disease, nerve damage, diabetic retinopathy, brain stroke, foot ulcer, etc. These risks factors can be reduced by early detections of disease. The big challenge for the health care industries nowadays is to give a more precise result which could easily predict whether a patient is having or diagnosed with such disease.

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Diabetes Prediction Using Novel Machine Learning Methods

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