Machines whisper before they scream: we built an AI model that predicts expensive problems

Periodic maintenance is common too, but still inefficient and often based on time, not actual machine condition. That ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...
IEEE

Hybrid Deep Reinforcement Learning for UAV Inspection in Large-Scale Wind Farms: Deployment and Routing Optimization

Abstract: The growth of global wind capacity necessitates efficient maintenance and inspection, particularly in offshore wind farms. However, existing manual inspection method is time consuming and ...
IEEE

An Exploratory Study of Security Vulnerabilities in Machine Learning Deployment Projects

Abstract: Machine learning (ML) deployment projects are used by practitioners to automatically deploy ML models. While ML deployment projects aid practitioners, security vulnerabilities in these ...
ascopubs.org

Development, External Validation, and Deployment of RFAN-ML: A Machine Learning Model to Estimate Renal Function After Nephrectomy

Reasoning Models for Text Mining in Oncology: A Comparison Between o1 Preview, GPT-4o, and GPT-5 at Different Reasoning Levels Partial nephrectomy has been advocated as the preferred surgical approach ...
FOX59 News

AgiBot Achieves First Real-World Deployment of Reinforcement Learning in Industrial Robotics

SHANGHAI, Nov. 2, 2025 /PRNewswire/ -- AgiBot, a robotics company specializing in embodied intelligence, announced a key milestone with the successful deployment of its Real-World Reinforcement ...