Frontiers

Risk factors for hematuria during indwelling urinary catheterization in acute myocardial infarction: a comparative analysis using logistic regression and decision tree

Objective: This study aimed to systematically identify risk factors for urinary catheter-related hematuria in patients with acute myocardial infarction (AMI). By integrating logistic regression and ...
IEEE

Road Accidents Prediction Using Decision Tree in Comparison to Linear Regression

Abstract: To reliably forecast traffic accidents using novel decision trees and evaluate their accuracy against linear regression. prediction of traffic accidents by the use of linear regression and ...
Scientific Research Publishing

Westreich, D., Lessler, J. and Funk, M.J. (2010) Propensity Score Estimation: Neural Networks, Support Vector Machines, Decision Trees (CART), and Meta-Classifiers as ...

ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...
Scientific Research Publishing

AI-Driven Mental Disorder Prediction: A Machine Learning Approach for Early Detection ()

1 Department of Neuroscience, Institute of Psychopathology, Rome, Italy. 2 Department of Computer Engineering (AI), University of Genova, Genova, Italy. Mental disorders, including depression, bipolar ...
Frontiers

Risk factors analysis of cognitive frailty among geriatric adults in nursing homes based on logistic regression and decision tree modeling

Objective: To investigate the risk factors associated with cognitive frailty among older adults in nursing homes using logistic regression and decision tree modeling, and to compare the predictive ...
IEEE

Improved Accuracy for prediction of leaf wetness using Logistic Regression algorithm compared with Decision Tree algorithm

Abstract: The main aim of this research work is to compare the accuracy percentage of leaf wetness predicted by the Novel Logistic Regression algorithm to that predicted by the Decision Tree method ...