Methods Two ophthalmologists without coding experience carried out AutoML model design using ... learning models devised by AI experts that were trained and validated on the data set from the ...

Background: This study investigated the cost-effectiveness and clinical impact of the 3E model (education, empowerment, and economy) in diabetes management using advanced machine learning techniques .

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 ...

Some communities use their monitoring data to provide ... wastewater applications typically consist of traditional machine learning (ML) to identify repeatable patterns and relationships in data to ...

mDepartment of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, ...

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 ...

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 ...

an iterative learning model predictive controller is constructed to achieve accurate and robust trajectory tracking control of an ankle rehabilitation robot driven by pneumatic muscle. Firstly, the ...