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 ...

With the growing demand for data privacy protection, traditional centralized machine learning methods have gradually exposed their limitations in the face of data privacy risks. In many practical ...

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