Characterizing genetic variants for clinical action

A Hybrid Classifier for Characterizing Motor Unit Action Potentials in Diagnosing Neuromuscular Disorders

Background: The time and frequency features of motor unit action potentials (MUAPs) extracted from electromyographic (EMG) signal provide discriminative information for diagnosis and treatment of neuromuscular disorders. However, the results of conventional automatic diagnosis methods using MUAP features is not convincing yet.Objective: The main goal in designing a MUAP characterization system ...

a hybrid classifier for characterizing motor unit action potentials in diagnosing neuromuscular disorders

background: the time and frequency features of motor unit action potentials (muaps) extracted from electromyographic (emg) signal provide discriminative information for diagnosis and treatment of neuromuscular disorders. however, the results of conventional automatic diagnosis methods using muap features is not convincing yet. objective: the main goal in designing a muap characterization system...

Characterizing the ADHD phenotype for genetic studies.

The genetic study of ADHD has made considerable progress. Further developments in the field will be reliant in part on identifying the most appropriate phenotypes for genetic analysis. The use of both categorical and dimensional measures of symptoms related to ADHD has been productive. The use of multiple reporters is a valuable feature of the characterization of psychopathology in children. It...

Pharmacogenomics of Thiopurine S-Methyltransferase: Clinical Applicability of Genetic Variants

Characterizing co-NL by a group action

In a recent paper (Girard 2012), Girard proposes to use his recent construction of a geometry of interaction in the hyperfinite factor (Girard 2011) in an innovative way to characterize complexity classes. We begin by giving a detailed explanation of both the choices and the motivations of Girard’s definitions. We then provide a complete proof that the complexity class co-NL can be characterize...