The purpose of the present study is to develop fast automated quantification of retinal fluid in optical coherence tomography (OCT) image sets. Fluid identification using our pipeline was tested on ...

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 ...

The progress in science and engineering increasingly depends on our ability to analyze massive amounts of observed and simulated data. The vast majority of this data, coming from high-performance high ...

High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...

The conditional mean of the response given the predictors is often of interest in regression problems. The central mean subspace, recently introduced by Cook and Li, allows inference about aspects of ...

Marketers must be deliberate when adding dimensions to a machine learning model. The cost of adding too many is accuracy. Decluttering fever is sweeping the country thanks to Marie Kondo. But clutter ...