Devdiscourse

Stacked AI model improves credit default forecasting

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...
IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
Frontiers

A clinical prediction model for delirium tremens: development and validation in alcohol-dependent patients using multivariable logistic regression

Delirium tremens (DT) is a severe complication of alcohol withdrawal. This study aimed to develop and validate a prediction model for DT risk in hospitalized patients with alcohol dependence, using ...
IEEE

Research on Tennis Match Momentum Prediction Based on Logistic Regression and GBDT Model

Abstract: Tennis is a complex sport where shifts in match momentum can dramatically alter the outcome of games. This paper aims to predict changes in momentum during tennis matches using Logistic ...