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

Abstract: Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large ...

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 ...

A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that leaf optical behavior can be accurately inferred from measurable phenotypic ...

Insights that answer the business questions above based on data analysis conducted. A predictive model that can classify individuals into two categories: depressed (label 1) and not depressed (label 0 ...

Background: The diagnosis-related groups prospective payment system (DRG-PPS) is widely implemented worldwide. Its core components include disease classification and pricing mechanisms. Developing a ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...

Municipal Solid Waste Generation (MSWG) presents a significant challenge for sustainable urban development, with waste production escalating at alarming rates worldwide. To address this issue, ...