Personalized Diabetes Prediction and Management System Using Machine Learning

EasyChair Preprint 14688

Abstract

Diabetes is a chronic metabolic disorder that requires individualized management strategies to achieve optimal patient outcomes. The aim of this project is to develop a personalized health recommendation system based on an individual health collection and predict whether the individual has diabetes or not. By dividing individuals into groups based on their health profile, the system can provide tailored advice specific to the characteristics of each group.The methods used in this project include Label Encoding, Normalization/Standardization, K-Means Clustering, the Elbow Method, Silhouette Analysis, Descriptive Statistics, Rule-based Recommendations

Keyphrases: Elbow Method, K-means clustering, Label Encoding, Random Forest, Silhouette Analysis, machine learning

@booklet{EasyChair:14688,
  author    = {K Dileep and K Srajan},
  title     = {Personalized Diabetes Prediction and Management System Using Machine Learning},
  howpublished = {EasyChair Preprint 14688},
  year      = {EasyChair, 2024}}