IEEE

Development and Evaluation of a Machine Learning Model for Cobot Action Prediction: Optimizing Algorithms Through Cognitive Workload Metrics

Abstract: Collaborative robots (Cobots) have replaced traditional industrial robots on the factory floors, enhancing automation and efficiency. From the perspective of Industry 5.0, centering around H ...
The Lancet

Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA: a multicentre study

Copyright: © 2025 The Author(s). Published by Elsevier Ltd.
Frontiers

Development of an interpretable machine learning model for predicting sarcopenia in patients undergoing maintenance hemodialysis

1 Department of Nephrology, Nanchong Central Hospital Affiliated to North Sichuan Medical College, Nanchong, China 2 Department of Nephrology, Guangyuan Central Hospital, Guangyuan, China Background: ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Objective: This study aimed to identify critical time points in SA-AKI progression development and validate dynamic, stratified machine learning prediction models for moderate-to-severe (Kidney ...
Frontiers

Development and validation of an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity: a cross-sectional study

Objective: To develop and validate an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity. Methods: A total of 471 older adults with ...
GEN

Arc Institute Launches Virtual Cell Challenge to Accelerate AI Model Development

Yusuf Roohani, PhD, machine learning group lead at the Arc Institute, is among a team of researchers training artificial intelligence (AI) models with transcriptome data to predict how cell gene ...
C&EN

Development of an Interpretable Machine Learning Model for Neurotoxicity Prediction of Environmentally Related Compounds

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, P. R. China Sino-Danish College, ...
GameSpot

Baldur's Gate 3 Dev Embraces Machine Learning For "Tasks That Nobody Wants To Do"

GameSpot may get a commission from retail offers. Machine-learning and artificial intelligence systems are some of the most-talked-about technologies in gaming--and across a variety of other ...
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 ...
GitHub

Machine Learning (ML) in Software Development

Machine learning (ML) is a subset of AI where a system learns patterns from data and makes decisions without being explicitly programmed for each outcome. In software development, this technology ...
C&EN

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery

The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly ...