Results 161 to 170 of about 2,032 (302)
Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin +11 more
wiley +1 more source
Robust Solutions of Optimization Problems Affected by Uncertain Probabilities
In this paper we focus on robust linear optimization problems with uncertainty regions defined by ø-divergences (for example, chi-squared, Hellinger, Kullback-Leibler).
De Waegenaere, A.M.B. +4 more
core
Risk-controlling Prediction with Distributionally Robust Optimization
International audienceConformal prediction is a popular paradigm to quantify the uncertainty of a model's output on a new batch of data. Quite differently, distributionally robust optimization aims at training a model that is robust to uncertainties in ...
Iutzeler, Franck, Mazoyer, Adrien
core +2 more sources
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
Approximation Algorithms for Distributionally Robust Stochastic Optimization [PDF]
Two-stage stochastic optimization is a widely used framework for modeling uncertainty, where we have a probability distribution over possible realizations of the data, called scenarios, and decisions are taken in two stages: we take first-stage actions ...
Linhares Rodrigues, Andre
core
Towards fair class-wise robustness: class optimal distribution adversarial training
Adversarial training has proven to be a highly effective method for improving the robustness of deep neural networks against adversarial attacks. Nonetheless, it has been observed to exhibit a limitation in terms of robust fairness, characterized by a ...
Hongxin Zhi +4 more
doaj +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
ABSTRACT Objective To determine whether integration of serum neurofilament light chain (NfL) and cortical dysfunction improves diagnostic accuracy in amyotrophic lateral sclerosis (ALS) when applied alongside the Gold Coast criteria (GCC). Methods In this prospective study, 148 participants with suspected ALS were recruited (101 ALS and 47 with ALS ...
Aicee Dawn Calma +16 more
wiley +1 more source
On the Power of Affine Policies in Two-Stage Adjustable Robust Optimization
Affine policies are widely used as a solution approach in dynamic optimization where computing an optimal adjustable solution is usually intractable. While the worst case performance of affine policies can be significantly bad, the empirical performance ...
Goyal, Vineet
core
Objective Sjögren's disease is an autoimmune disorder that can impact multiple organ systems, including the peripheral nervous system (PNS). PNS manifestations, which can exist concurrently, include mononeuropathies, polyneuropathies, and autonomic nervous system neuropathies.
Anahita Deboo +88 more
wiley +1 more source

