Results 141 to 150 of about 33,603 (293)

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein   +7 more
wiley   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

open access: yesAnnals 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

Feedback-integrated prompt optimiser for problem formulation. [PDF]

open access: yesSci Rep
Amarasinghe PT   +3 more
europepmc   +1 more source

In‐Depth Profiling Highlights the Effect of Efgartigimod on Peripheral Innate and Adaptive Immune Cells in Myasthenia Gravis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is an autoimmune disorder characterized by antibody‐mediated complement activation. Efgartigimod, a neonatal Fc receptor (FcRn) antagonist, is approved for treating generalized MG (gMG). However, its modulatory effects on upstream innate and adaptive immune cells remain largely unexplored.
Lei Jin   +11 more
wiley   +1 more source

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

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