Abstract: This study investigates the application of the Variational Autoencoder (VAE) model for classifying lung images obtained from chest X-ray data, with a primary focus on utilizing the encoder ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

Thrombotic thrombocytopenic purpura (TTP) is a rare, life threatening thrombotic microangiopathy that requires prompt diagnosis to reduce mortality. However, its early identification is often hindered ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Abstract: In a complex context with many classes and instances, synthetic classification evaluation techniques (e.g. classical measures made from confusion matrix) often obscure important information.

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.

However color scaling is hard to interpret, and spatial cues are easier to help interpret quantities than color variations. The number represented in each box represent absolute ones, while one may be ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...