By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...
The development of glmSMA represents a valuable advancement in spatial transcriptomics analysis, offering a mathematically robust regression-based approach that achieves higher-resolution mapping of ...
Background: Patients with persistent atrial fibrillation (PsAF) exhibit a high recurrence rate following catheter ablation, and there is a lack of individualized prediction tools based on clinical ...
The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...
1 School of Mathematics and Statistics, Guilin University of Technology, Guilin, China. 2 Applied Statistics Institute, Guilin University of Technology, Guilin, China.. Current high-dimensional ...
Abstract: It has been observed that the performances of many high-dimensional estimation problems are universal with respect to underlying sensing (or design) matrices. Specifically, matrices with ...
Jeremy has more than 2200 published articles on Collider to his name, and has been writing for the site since February 2022. He's an omnivore when it comes to his movie-watching diet, so will gladly ...
Prior to PILOT, fitting linear model trees was slow and prone to overfitting, especially with large datasets. Traditional regression trees struggled to capture linear relationships effectively. Linear ...
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