IEEE

Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries

Abstract: Accurate estimation of State-of-Charge (SoC) and core temperature is fundamental to optimizing the performance, safety, and longevity of Lithium-Ion Batteries (LiBs), particularly in ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Frontiers

Construction of a prediction model for sarcopenic obesity based on machine learning

1 Department of Health Care/Geriatrics, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China 2 Qingdao University, Qingdao, Shandong Province, China Background: In the context ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
marktechpost

This AI Paper from Weco AI Introduces AIDE: A Tree-Search-Based AI Agent for Automating Machine Learning Engineering

The development of high-performing machine learning models remains a time-consuming and resource-intensive process. Engineers and researchers spend significant time fine-tuning models, optimizing ...
BMJ

Predictive machine-learning model for screening iron deficiency without anaemia: a retrospective cohort study

Objectives This study aimed to develop and validate a machine-learning (ML) model to predict iron deficiency without anaemia (IDWA) using routinely collected electronic health record (EHR) data. The ...