Results 51 to 60 of about 259,894 (334)
Sparse Ordinal Logistic Regression and Its Application to Brain Decoding
Frontiers in Neuroinformatics, 2018 Brain decoding with multivariate classification and regression has provided a powerful framework for characterizing information encoded in population neural activity.
Emi Satake +4 more
doaj +1 more source
Ordinal Regression Based Subpixel Shift Estimation for Video Super-Resolution
EURASIP Journal on Advances in Signal Processing, 2007 We present a supervised learning-based approach for subpixel motion estimation which is then used to perform video super-resolution. The novelty of this work is the formulation of the problem of subpixel motion estimation in a ranking framework.
Nemanja Petrovic +3 more
doaj +2 more sources
Robust Image Ordinal Regression with Controllable Image Generation [PDF]
, 2023 Yi Cheng +7 more
openalex +3 more sources
Selection of Ordinally Scaled Independent Variables [PDF]
, 2009 Ordinal categorial variables are a common case in regression modeling. Although the case of ordinal response variables has been well investigated, less work has been done concerning ordinal predictors.
Gertheiss, Jan +3 more
core +1 more source
mvord: An R Package for Fitting Multivariate Ordinal Regression Models
Journal of Statistical Software, 2020 The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link.
Rainer Hirk, Kurt Hornik, Laura Vana
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Apolipoprotein ε4 (APOE ε4) is a potent genetic risk factor for Alzheimer's disease (AD). However, its role in cerebral small vessel disease (CSVD) remains unclear. Given the clinical and pathological similarities between CSVD and AD, this study aimed to investigate the associations of APOE ε4 gene dosage with cognitive function and
Tingru Jin +6 more
wiley +1 more source
MANAS: Journal of Engineering, 2022 In cases where the dependent variable is categorical and ordinal, the Ordinal Logistic Regression Model is used for model estimation. In order to predict the Ordinal Logistic Regression Model, it must provide the parallel lines assumption.
Burak Uyar, Cevdet Büyüksu
doaj +1 more source
Ordinal Regression by Extended Binary Classification [PDF]
, 2007 We present a reduction framework from ordinal regression to binary classification based on extended examples. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended ...
Li, Ling, Lin, Hsuan-Tien
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Aims This study aimed to explore the relationship between stress‐induced hyperglycemia (SIH) and in‐hospital medical complications in patients with acute stroke. Methods We enrolled 865,765 patients with acute stroke from the Chinese Stroke Center Alliance cohort.
Xintong Song +6 more
wiley +1 more source
Portable Low‐Field Magnetic Resonance Imaging in People With Human Immunodeficiency Virus
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective The aging population of people with HIV (PWH) raises heightened concerns regarding accelerated aging and dementia. Portable, low‐field MRI (LF‐MRI) is an innovative technology that could enhance access and facilitate routine monitoring of PWH.
Annabel Sorby‐Adams +14 more
wiley +1 more source