If data used to train artificial intelligence models for medical applications, such as hospitals across the Greater Toronto ...

Early prediction of in-hospital pneumonia mortality can effectively be done using a machine learning (ML) model based on clinical data.

The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the medical field because ...

Abstract: Model-predictive control (MPC) is becoming increasingly popular in addressing the consensus problem of multiagent systems (MASs) due to its ability to manage constraints in a multivariable ...

Machine learning techniques have garnered widespread attention due to their advantages in modeling high-dimensional, heterogeneous data.Objective: This study was to evaluate the predictive capability ...

Designed to support the entire machine learning lifecycle -- from data ingestion and model training to deployment and monitoring -- Azure ML is empowering developers to integrate predictive ...

This review provides a thorough and organized overview of machine learning ... on ML model accuracy, while this review focuses on actual clinical application. Explains how different hospitals, medical ...

In this article, a 5G aware real-time diabetes prediction framework is proposed using optimized bidirectional long short-term memory (Bi-LSTM) with deep reinforcement learning (DRL ... and optimize ...