New research from the Myasthenia Gravis Rare Disease Network (MGNet). This summary is based on a paper published in the journal Muscle & Nerve on April 2, 2025, titled "Concordance between radioimmunoassay and fixed cell-based assay in subjects without myasthenia gravis: optimizing the diagnostic approach." 

Read the paper here. 

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Transcript:

New research from the Myasthenia Gravis Rare Disease Network (MGNet), a research group of the Rare Diseases Clinical Research Network. 

Developing an Artificial Intelligence-Based Assessment of Telehealth Examinations in Myasthenia Gravis. 

This summary is based on a paper published in the journal Muscle & Nerve on April 2, 2025.  

Myasthenia gravis (MG) is a neuromuscular disorder caused by an autoimmune response which blocks or damages acetylcholine receptors in muscles, causing disabling weakness. Although telemedicine is considered a positive tool for both MG patients and physicians, not much is known about its strengths and limitations for MG examinations.

In this study, researchers developed an artificial intelligence-based assessment of telehealth examinations in MG. The team studied video recordings of 51 patients with MG who completed two telemedicine-based examinations with neuromuscular experts. Researchers applied artificial intelligence algorithms including computer vision, speech analysis, and natural language processing to assess the reproducibility and reliability of the examinations.

Results showed that overall MG core examination scores were consistent across examiners. However, individual metrics showed up to 25% variability due to differences in examiner instructions, video recording limitations, and patient disease severity. Authors note that further refinement of this technology could enhance examiner training and reduce variability in clinical trial outcome measures.