AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Opinion
Dot Physics on MSNOpinion

Understanding line integrals through the field X × Y X̂ – Y X̂

Gain a clear understanding of line integrals through the vector field 𝐹 = 𝑋 𝑖 ^ × 𝑌 𝑖 ^ − 𝑌 𝑖 ^ F=X i ^ ×Y i ^ −Y i ^ in this detailed physics and math tutorial. This video breaks down the ...
EurekAlert!

Novel laboratory-based risk scores predicts mortality in patients with COVID-19

The GENCOV study developed clinical laboratory‑based risk scores to predict mortality among hospitalized COVID‑19 patients in ...
IEEE

Multivariate Time Series Forecasting Using Multiscale Recurrent Networks With Scale Attention and Cross-Scale Guidance

Abstract: Multivariate time series (MTS) forecasting is considered as a challenging task due to complex and nonlinear interdependencies between time steps and series. With the advance of deep learning ...
IEEE

A Gaussian Integral Filter with Multivariate Laplace Process Noise

This paper introduces the concept of the Gaussian integral filter (GIF), the limit of the Gaussian sum filter (GSF) for when the number of mixands tends to infinity. The GIF is obtained via a ...
GitHub

AERCA: Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery (ICLR 2025 Oral)

The AERCA algorithm performs robust root cause analysis in multivariate time series data by leveraging Granger causal discovery methods. This implementation in PyTorch facilitates experimentation on ...