Background: In recent years, machine learning (ML)–based models have been widely used in clinical domains to predict clinical risk events. However, in production, the performances of such models ...

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

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 letter presents the development of a multiple-input multiple-output (MIMO) coupling controller for the independent-setup variable stiffness actuator (VSA). The dynamic model of the ...

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 ...

Abstract: This study addresses detecting multiple targets in the presence of signal-dependent clutter using a multiple-input–multiple-output radar system. Our primary objective is to design transmit ...

The Department of Health and Human Services' (HHS') health tech arm wants to hear from the healthcare industry about ways to speed up the adoption of artificial intelligence in medical treatment. The ...