Results 31 to 40 of about 4,642 (256)

Robust and Sparse Regression via γ-Divergence

Entropy, 2017
In high-dimensional data, many sparse regression methods have been proposed. However, they may not be robust against outliers. Recently, the use of density power weight has been studied for robust parameter estimation, and the corresponding divergences ...
Takayuki Kawashima, Hironori Fujisawa
doaj   +1 more source

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

Aging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss, Alexis C. Wardell, Allison M. Deal, Kirsten A. Nyrop, Allison Ross, Yara G. Abdou, Jeffrey D. Aldrich, Lisa A. Cary, E. Claire Dees, Katherine E. Reeder‐Hayes, Emily M. Ray, Natalia Mitin, Denis Tsygankov   +12 more
wiley   +1 more source

Adaptive Monotone Shrinkage for Regression

, 2015
We develop an adaptive monotone shrinkage estimator for regression models with the following characteristics: i) dense coefficients with small but important effects; ii) a priori ordering that indicates the probable predictive importance of the features.
Zhuang Ma, Dean P. Foster, Robert A. Stine   +2 more
openaire   +3 more sources

Evaluation of Digital Technologies for Home‐Based Assessment in People With Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller, Vanessa Vallejo, Mónica Povedano Panadés, Orla Hardiman, Véronique Danel‐Brunaud, Senda Ajroud‐Driss, Philippe Couratier, Jeremy Shefner, Anna Gokey, Mike DiCesare, Erin Lennox, Jens Praestgaard, Lucie Brujin, Peggy Allred, Ram Miller   +14 more
wiley   +1 more source

Multi-Physics Monotone Score Transport for Unsupervised Domain Adaptation of Continuous Tool Wear Prediction

Sensors
Cross-material continuous tool wear prediction is difficult because a model must preserve the physical wear scale, not only align high-dimensional sensor features.
Enhao Cui, Runshan Hu, Weina Zhang, Zihan Fei, Chenyang Zhu   +4 more
doaj   +1 more source

Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data

Stats, 2022
Panel count data often occur in a long-term recurrent event study, where the exact occurrence time of the recurrent events is unknown, but only the occurrence count between any two adjacent observation time points is recorded.
Chunling Wang, Xiaoyan Lin
doaj   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Multi-quantile systemic financial risk based on a monotone composite quantile regression neural network

Frontiers in Physics
This study proposes a novel perspective to calibrate the conditional value at risk (CoVaR) of countries based on the monotone composite quantile regression neural network (MCQRNN).
Chao Ren, Ziyan Zhu, Donghai Zhou
doaj   +1 more source

On estimation for accelerated failure time models with small or rare event survival data

BMC Medical Research Methodology, 2022
Background Separation or monotone likelihood may exist in fitting process of the accelerated failure time (AFT) model using maximum likelihood approach when sample size is small and/or rate of censoring is high (rare event) or there is at least one ...
Tasneem Fatima Alam, M. Shafiqur Rahman, Wasimul Bari   +2 more
doaj   +1 more source

White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram, Guangwei Du, Sangam Kanekar, Nandakumar Nagaraja   +3 more
wiley   +1 more source