Results 51 to 60 of about 670,318 (234)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
Learning curve assessment of rule use provides evidence for spared implicit sequence learning in a mouse model of mental retardation [PDF]
, 2009 Humans with Fragile X Syndrome (FXS) have a mental retardation of which a notable characteristic is a weakness in recalling sequences of information. A mouse model of the disorder exists which exhibits behavioral and neurologic changes, but cognitive ...
Bauchwitz, Dr. Robert
core
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source
Learning curves for Soft Margin Classifiers
, 2002 Typical learning curves for Soft Margin Classifiers (SMCs) learning both realizable and unrealizable tasks are determined using the tools of Statistical Mechanics.
Gordon, Mirta B. +1 more
core +1 more source
Asymptotic Learning Curve and Renormalizable Condition in Statistical Learning Theory
, 2010 Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovered that the asymptotic learning curves in Bayes estimation are subject to a
Bernstein I N +10 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu +10 more
wiley +1 more source
The Perils of the Learning Model For Modeling Endogenous Technological Change [PDF]
Learning or experience curves are widely used to estimate cost functions in manufacturing modeling. They have recently been introduced in policy models of energy and global warming economics to make the process of technological change endogenous.
William D. Nordhaus
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Gaussian Process Regression with Mismatched Models [PDF]
, 2001 Learning curves for Gaussian process regression are well understood when the `student' model happens to match the `teacher' (true data generation process). I derive approximations to the learning curves for the more generic case of mismatched models, and
Sollich, Peter
core +1 more source
Clinically Relevant Outcome Measures in Women With Adrenoleukodystrophy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Adrenoleukodystrophy is a rare inherited peroxisomal disease caused by pathogenic variants in the ABCD1 gene located on the X chromosome. Although the most severe central nervous system and adrenal complications typically affect only men with adrenoleukodystrophy, the majority of women develop myeloneuropathy symptoms in adulthood.
Chenwei Yan +3 more
wiley +1 more source
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves
, 2019 Estimating what would be an individual's potential response to varying levels of exposure to a treatment is of high practical relevance for several important fields, such as healthcare, economics and public policy.
Bauer, Stefan +4 more
core +1 more source