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

Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...

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: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...

We evaluated machine learning algorithms (random forest [RF], extra-trees classifier, and light gradient boosting machine) and selected the RF model as the final model based on its performance. To ...

Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...