This study presents valuable findings for identifying biotypes of depression patients using white matter measures, which are under-utilised and under-appreciated in current biological and ...

The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

New 100 mg/dL Target Glucose setting offers more customization and tighter glucose management. Enhanced algorithm helps users remain in Automated Mode to improve the user experience. Most requested ...

Datasets often incorporate various functional patterns related to different aspects or regimes, which are typically not equally present throughout the dataset. We propose a novel partitioning ...

ABSTRACT: Background: Unjustified emergency department (ED) visits are a global issue, contributing to overcrowding, reduced care quality, decreased patient satisfaction, and increased healthcare ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...

Abstract: Graph partitioning used in many fields is an important problem in graph theory so that an efficient algorithm for graph partitioning is meaningful. But graph partitioning is a NP-complete ...