Objective Patients with atrial fibrillation (AF) frequently have multiple comorbidities that increase the risk of hospitalisation and contribute to higher mortality. However, studies examining the ...
TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...
Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...
Proteomic analysis (proteomics) refers to the systematic identification and quantification of the complete complement of proteins (the proteome) of a biological system (cell, tissue, organ, biological ...
Several measurement techniques used in the life sciences gather data for many more variables per sample than the typical number of samples assayed. For instance, DNA microarrays and mass spectrometers ...
Objectives To explore the levels of health-related functioning during pregnancy and postpartum and its association with non-severe maternal morbidities. Design An observational longitudinal study.
Companies say AI will fundamentally change business forever. But what does that change look like, and what are they doing to make it happen? Plus, teen AI founders, humanoid-robot hype, Nvidia’s fresh ...
Get alerts on the UK app about the latest stories from InDepth - the home of the best analysis from BBC correspondents Fergal Keane has met thousands of traumatised children while reporting on ...
Abstract: Multivariate time series classification (MTSC) based on deep learning (DL) has attracted increasingly more research attention. The performance of a DL-based MTSC algorithm is heavily ...
Abstract: The findings of the empirical work focus mainly on establishing how much a multi-class categorization model benefits various populations. The model can appropriately describe the following ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback