Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.
Professor Klaus Nordhausen develops modern multivariate statistical methods to analyze high-dimensional and large datasets in different fields.
The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...
In patients with high PD-L1 expression identified before surgery, clinicians should consider the possibility of lymph node metastasis when determining surgical strategy, including the extent of lymph ...
Registry-based data indicate that comorbid sleep disorders are common in severe asthma and are associated with significantly ...
A research team introduces a fully automated, non-destructive phenotyping platform that combines X-ray fluorescence microscopy with computer vision and machine learning.
Researchers from The University of Osaka find that migration of blood sugar to saliva in individuals with type 2 diabetes ...
Background Despite anticoagulation, patients with atrial fibrillation (AF) experience persistent elevated cardiovascular risk ...
Background Multiple long-term conditions (MLTCs) are common among individuals with heart failure (HF); however, the influence ...
Health Insurance Equity, Social Determinants, Socioeconomic Status, Insurance Quality, Urban-Rural Disparity, Hukou, China ...
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