Nature

Evaluating distributed-learning on real-world obstetrics data: comparing distributed, centralized and local models

This study focused on comparing distributed learning models with centralized and local models, assessing their efficacy in predicting specific delivery and patient-related outcomes in obstetrics using ...
EurekAlert!

A new era for green and intelligent transportation: LoRa meets distributed machine learning

In a world where urban traffic congestion and environmental concerns are escalating, innovative solutions are crucial for creating sustainable and efficient transportation systems. A groundbreaking ...
Nature

Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals

Quality improvement, clinical research, and patient care can be supported by medical predictive analytics. Predictive models can be improved by integrating more patient records from different ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...