Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

In this retrospective cohort analysis, researchers aimed to identify key predictors of trial enrollment among cancer patients.

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

ABSTRACT: Postoperative nausea and vomiting (PONV) is a common complication after anesthesia and surgery. Traditional predictive models, such as Apfel scores, rely on linear assumptions and limited ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

LB Beistad is a writer and musician based in Nashville, TN. Her love of gaming began with her cousin introducing her to Banjo Kazooie and Jak and Daxter. It was love at first play. Since then, she has ...

Introduction: This study aimed to develop a diabetic retinopathy (DR) Prediction model using various machine learning algorithms incorporating the novel predictor Triglyceride-glucose index (TyG).

Abstract: In the field of radio technology, the scarcity of spectrum resources has become increasingly severe, while demands for higher accuracy and speed in spectrum sensing technologies continue to ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...