AIMC Topic: Muscular Dystrophies

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Emerging therapeutic strategies in muscular dystrophy: an updated review on pathogenesis and treatment advances.

Molecular biology reports
Muscular dystrophy (MD) comprises a class of genetic conditions characterized by the progressive degeneration and weakness of skeletal muscle. Genetic etiologies differ among the major muscular dystrophies: myotonic dystrophy type 1 (DM1) is linked t...

Integrated phenotypic and transcriptomic characterization of desmin-related cardiomyopathy in hiPSC-derived cardiomyocytes and machine learning-based classification of disease features.

European journal of cell biology
Desmin-related diseases are characterized by skeletal muscle weakness, cardiomyopathy, and respiratory dysfunction due to mutations in the desmin gene (DES), which encodes a protein essential for muscle cell integrity. This study investigates the eff...

The artificial intelligence challenge in rare disease diagnosis: A case study on collagen VI muscular dystrophy.

Computers in biology and medicine
The use of artificial intelligence (AI) techniques is significantly changing the analysis of medical images, accelerating and standardizing the diagnosis process. To train an AI model, however, a large dataset is typically required, especially when u...

Combining electromyographic and electrical impedance data sets through machine learning: A study in D2-mdx and wild-type mice.

Muscle & nerve
INTRODUCTION/AIMS: Needle impedance-electromyography (iEMG) assesses the active and passive electrical properties of muscles concurrently by using a novel needle with six electrodes, two for EMG and four for electrical impedance myography (EIM). Here...

A deep learning model for diagnosing dystrophinopathies on thigh muscle MRI images.

BMC neurology
BACKGROUND: Dystrophinopathies are the most common type of inherited muscular diseases. Muscle biopsy and genetic tests are effective to diagnose the disease but cost much more than primary hospitals can reach. The more available muscle MRI is promis...

Accuracy of a machine learning muscle MRI-based tool for the diagnosis of muscular dystrophies.

Neurology
OBJECTIVE: Genetic diagnosis of muscular dystrophies (MDs) has classically been guided by clinical presentation, muscle biopsy, and muscle MRI data. Muscle MRI suggests diagnosis based on the pattern of muscle fatty replacement. However, patterns ove...

A neural network approach to analyze cross-sections of muscle fibers in pathological images.

Computers in biology and medicine
Morphological characteristics of muscle fibers, such as their cross-sections, are important indicators of the health and function of the musculoskeletal system. However, manual analysis of muscle fiber morphology is a labor-intensive and time-consumi...

A Novel Hybrid Feature Selection Model for Classification of Neuromuscular Dystrophies Using Bhattacharyya Coefficient, Genetic Algorithm and Radial Basis Function Based Support Vector Machine.

Interdisciplinary sciences, computational life sciences
An accurate classification of neuromuscular disorders is important in providing proper treatment facilities to the patients. Recently, the microarray technology is employed to monitor the level of activity or expression of large number of genes simul...