Electrodiagnostic subtyping in Guillain-Barré syndrome patients in the International Guillain-Barré Outcome Study.

Background And Purpose: Various electrodiagnostic criteria have been developed in Guillain-Barré syndrome (GBS). Their performance in a broad representation of GBS patients has not been evaluated. Motor conduction data from the International GBS Outcome Study (IGOS) cohort were used to compare two widely used criterion sets and relate these to diagnostic amyotrophic lateral sclerosis criteria.

Challenges in the Early Diagnosis and Treatment of Chronic Inflammatory Demyelinating Polyradiculoneuropathy in Adults: Current Perspectives.

Diagnosing Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) poses numerous challenges. The heterogeneous presentations of CIDP variants, its mimics, and the complexity of interpreting electrodiagnostic criteria are just a few of the many reasons for misdiagnoses. Early recognition and treatment are important to reduce the risk of irreversible axonal damage, which may lead to permanent disability.

Artificial intelligence for automatic classification of needle EMG signals: A scoping review.

Objective: This scoping review provides an overview of artificial intelligence (AI), including machine and deep learning techniques, in the interpretation of clinical needle electromyography (nEMG) signals.

Methods: A comprehensive search of Medline, Embase and Web of Science was conducted to find peer-reviewed journal articles. All papers published after 2010 were included.

Artificial intelligence-based classification of motor unit action potentials in real-world needle EMG recordings.

Objective: To develop an artificial neural network (ANN) for classification of motor unit action potential (MUAP) duration in real-word, unselected and uncleaned needle electromyography (n-EMG) recordings.

Methods: Two nested ANN models were trained, the first discerning muscle rest, contraction and artifacts in n-EMG recordings from 2674 individual muscles from 326 patients obtained as part of daily care. The second ANN model subsequently used segments labeled as contraction for prediction of prolonged, normal and shortened MUAPs.