A REVIEW ON APPLICATIONS OF MACHINE LEARNING TECHNIQUES IN DIABETES HANDLING

A REVIEW ON APPLICATIONS OF MACHINE LEARNING TECHNIQUES IN DIABETES HANDLING
Author(s):
Samridhi Puri, Satinder Kaur , Satveer Kour, Kumari Sarita
Keywords:
Machine learning, Diabetes mellitus, Support Vector Machine, Random Forest
Abstract
Diabetes mellitus is a chronic metabolic disorder affecting millions of people worldwide. Early diagnosis and effective management of diabetes are crucial to prevent complications and improve patient outcomes. In recent years, the integration of machine learning (ML) techniques has shown promising results in aiding diabetes diagnosis and management. Various Machine learning techniques can be used like Support Vector Machine (SVM), K Nearest Neighbour (KNN), Random Forest, Decision Tree in detection and treatment of diabetes mellitus. This paper provides an overview of different machine learning applications used in diabetes handling. In addition, it also discusses how to use ML in this discipline. It is concluded that ML techniques is a good approach for controlling diabetes mellitus at an early stage.
Article Details
Unique Paper ID: 164117 Publication Volume & Issue: Volume 10, Issue 12 Page(s): 181 - 184
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