The issue of malnutrition in children poses a serious challenge in the effort to achieve the
well-being and development of a smart generation of children. Central Java is a province on …

A digitalização na saúde, impulsionada por appse dispositivos móveis, mudou
comportamentos, fazendo dos pacientes protagonistas na medicina preventiva. O …

We leveraged machine learning (ML) techniques, namely logistic regression (LR), random
forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and …

This thesis explores the potential of artificial intelligence in early diabetes prediction,
highlighting innovative contributions while utilizing various databases. The first two …

The global prevalence of diabetes mellitus poses a significant public health challenge. This
study aims to use dimensionality reduction methods with machine learning (ML) algorithms …

Predictive maintenance is a method used to analyze the real-time and historical data from
the various sensors deployed in critical areas of a machinery to detect the failures and their …

The study was conducted during 2022-23 to assess the level of food insecurity and income
status among farm households. Data from 474 farmers through personal interview method …

Early diabetes identification is crucial for controlling chronic illnesses. This study uses WEKA
to compare the performance of four classification algorithms (Multilayer Perceptron, Logistic …

Advancements in biotechnology and public health technologies have significantly increased
public health data, aiding early disease detection and prevention, particularly in diabetes …

Aim: Diabetes mellitus is a metabolic disease caused by elevated blood sugar. If this
disease is not diagnosed on time, it has the potential to pose a risk to other organs and …