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
The Core of a 2-Dimensional Set-Valued Mapping. Existence Criteria and Efficient Algorithms for Lipschitz Selections of Low Dimensional Set-Valued Mappings [PDF]
Pavel Shvartsman
openalex +1 more source
Reduced Muscular Carnosine in Proximal Myotonic Myopathy—A Pilot 1H‐MRS Study
ABSTRACT Objective Myotonic dystrophy type 2 (proximal myotonic myopathy, PROMM) is a progressive multisystem disorder with muscular symptoms (proximal weakness, pain, myotonia) and systemic manifestations such as diabetes mellitus, cataracts, and cardiac arrhythmias.
Alexander Gussew +11 more
wiley +1 more source
Modeling biological memory network by an autonomous and adaptive multi-agent system
At the intersection of computation and cognitive science, graph theory is utilized as a formalized description of complex relationships description of complex relationships and structures, but traditional graph models are static, lack the dynamic and ...
Hui Wei, Chenyue Feng, Fushun Li
doaj +1 more source
Improving pattern tracking with a language-aware tree differencing algorithm
Nicolas Palix +2 more
openalex +2 more sources
A Posteriori Error Estimation and Adaptive Algorithm for the Atomistic/Continuum Coupling in 2D [PDF]
Hao Wang +3 more
openalex +1 more source
Association of Corticospinal Tract Asymmetry With Ambulatory Ability After Intracerebral Hemorrhage
ABSTRACT Background Ambulatory ability after intracerebral hemorrhage (ICH) is important to patients. We tested whether asymmetry between ipsi‐ and contra‐lesional corticospinal tracts (CSTs) assessed by diffusion tensor imaging (DTI) is associated with post‐ICH ambulation.
Yasmin N. Aziz +25 more
wiley +1 more source
Explainable representation learning of small quantum states
Unsupervised machine learning models build an internal representation of their training data without the need for explicit human guidance or feature engineering.
Felix Frohnert, Evert van Nieuwenburg
doaj +1 more source
A Note on the Performance of Algorithms for Solving Linear Diophantine Equations in the Naturals [PDF]
Valeriu Motroi, Ştefan Ciobâcă
openalex +1 more source

