Objective: This study aims to develop and internally validate a multivariable logistic regression model and a simplified scoring system, based on standardized ultrasonographic features, for the ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

This project aims to build a multi-class text classification model for consumer complaint narratives.It categorizes complaints into four classes: Credit Reporting, Debt Collection, Consumer Loan, and ...

Abstract: In this paper, the cyclists’ decision-making behavior in the interaction with a car at unsignaled intersection is measured and analyzed. Based on the measured data, the cyclists’ ...

Abstract: The purpose of this work is to investigate the effectiveness of DensNet and Logistic Regression in terms of accurately predicting the classification of footwear trends.In this study, there ...

Objective: This study aimed to develop and validate a multivariate logistic regression model for predicting intracranial aneurysm (IA) rupture by integrating clinical data, aneurysm morphology, and ...

ABSTRACT: Objective: Our study aims to validate the subjective Bayes mathematical model using the mathematical model of logistic regression. Expert systems are being utilized increasingly in medical ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...