Results 151 to 160 of about 317,020 (282)

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

open access: yesAnnals 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

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

open access: yesAnnals 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

Editorial: Deep neural network architectures and reservoir computing

open access: yesFrontiers in Artificial Intelligence
Sou Nobukawa   +7 more
doaj   +1 more source

Physical echo state network based on the nonlinearity and dynamic response of ambipolar heterostructure transistors. [PDF]

open access: yesNat Commun
Zhong WM   +8 more
europepmc   +1 more source

Traumatic Microhemorrhages Are Not Synonymous With Axonal Injury

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Diffuse axonal injury (DAI) is caused by acceleration‐deceleration forces during trauma that shear white matter tracts. Susceptibility‐weighted MRI (SWI) identifies microbleeds that are considered the radiologic hallmark of DAI and are used in clinical prognostication.
Karinn Sytsma   +9 more
wiley   +1 more source

Generalization and systematicity in echo state networks

open access: yes, 2008
Echo state networks (ESNs) are recurrent neural networks that can be trained efficiently because the weights of recurrent connections remain fixed at random values. Investigations of these networks' ability to generalize in sentence-processing tasks have resulted in mixed outcomes. Here, we argue that ESNs do generalize but that they are not systematic,
Frank, S.L., Čerňanský, M.
openaire   +2 more sources

Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler   +20 more
wiley   +1 more source

Input driven optimization of echo state network parameters for prediction on chaotic time series. [PDF]

open access: yesSci Rep
Gonbadi L   +5 more
europepmc   +1 more source

Brainstem and Cerebellar Volume Loss and Associated Clinical Features in Progressive Supranuclear Palsy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Progressive Supranuclear Palsy (PSP) is a neurodegenerative ‘tauopathy’ with predominating pathology in the basal ganglia and midbrain. Caudal tau spread frequently implicates the cerebellum; however, the pattern of atrophy remains equivocal.
Chloe Spiegel   +8 more
wiley   +1 more source

Forecast of Aging of PEMFCs Based on CEEMD-VMD and Triple Echo State Network. [PDF]

open access: yesSensors (Basel)
Sun J   +9 more
europepmc   +1 more source

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