Abstract: Large-scale sparse multiobjective optimization problems (LSMOPs) are of great significance in the context of practical applications, such as critical node detection, feature selection, and ...
This study aims to improve survival modeling in head and neck cancer (HNC) by integrating patient-reported outcomes (PROs) using dimensionality reduction techniques. PROs capture symptom severity ...
A new study from researchers at the Johns Hopkins Bloomberg School of Public Health sheds light on how people who inject drugs (PWID) are responding to the growing instability and danger in the U.S.
Republican leadership in the Ways and Means committee of the U.S. House of Representatives released Monday night a draft of a reconciliation bill that seeks to undo much of the Inflation Reduction Act ...
Department of Chemistry and Biochemistry, School of Sciences and Technology, São Paulo State University (UNESP), Presidente Prudente 19060-900, Brazil Institute of Biosciences, Humanities and Exact ...
Forbes contributors publish independent expert analyses and insights. author of Chained to the Desk in a Hybrid World: A Guide to Balance. April is Stress Awareness Month—dedicated to raising ...
Abstract: Dimensionality reduction can be applied to hyperspectral images so that the most useful data can be extracted and processed more quickly. This is critical in any situation in which data ...
Forbes contributors publish independent expert analyses and insights. Greg Licholai writes and teaches about innovation in healthcare. In 2022, the Biden Administration enacted the Inflation Reduction ...
Here, we present Randomized Spatial PCA (RASP), a novel spatially aware dimensionality reduction method for spatial transcriptomics (ST) data. RASP is designed to be orders-of-magnitude faster than ...
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