Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification of Skeletal Muscle Fibers01:48

Classification of Skeletal Muscle Fibers

56.8K
Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...
56.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Visualizing Muscle Sialic Acid Expression in the GNED207VTgGne-/- Cmah-/- Model of GNE Myopathy: A Comparison of Dietary and Gene Therapy Approaches.

Journal of neuromuscular diseases·2021
Same author

FKRP mutations cause congenital muscular dystrophy 1C and limb-girdle muscular dystrophy 2I in Asian patients.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia·2021
Same author

A recurrent homozygous ACTN2 variant associated with core myopathy.

Acta neuropathologica·2021
Same author

Neuropathy/intranuclear inclusion bodies in oculopharyngodistal myopathy: A case report.

eNeurologicalSci·2021
Same author

Myoclonic Epilepsy with Ragged-red Fibers with Intranuclear Inclusions.

Internal medicine (Tokyo, Japan)·2021
Same author

A novel RyR1-selective inhibitor prevents and rescues sudden death in mouse models of malignant hyperthermia and heat stroke.

Nature communications·2021

Related Experiment Video

Updated: Sep 2, 2025

Human Vastus Lateralis Skeletal Muscle Biopsy Using the Weil-Blakesley Conchotome
07:16

Human Vastus Lateralis Skeletal Muscle Biopsy Using the Weil-Blakesley Conchotome

Published on: March 4, 2016

16.9K

[Development of Deep Convolutional Neural Network-Based Algorithm for Muscle Biopsy Diagnosis].

Mariko Okubo1, Yoshinori Kabeya, Ichizo Nishino

  • 1Department of Neuromuscular Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry.

Brain and Nerve = Shinkei Kenkyu No Shinpo
|August 9, 2022
PubMed
Summary

Artificial intelligence can aid in diagnosing muscle diseases. A deep learning algorithm for muscle biopsy analysis demonstrated superior accuracy compared to physicians, improving diagnostic capabilities.

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.9K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Related Experiment Videos

Last Updated: Sep 2, 2025

Human Vastus Lateralis Skeletal Muscle Biopsy Using the Weil-Blakesley Conchotome
07:16

Human Vastus Lateralis Skeletal Muscle Biopsy Using the Weil-Blakesley Conchotome

Published on: March 4, 2016

16.9K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.9K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Area of Science:

  • Medical diagnostics
  • Pathology
  • Artificial Intelligence in Medicine

Background:

  • Histopathologic evaluation of muscle biopsy is crucial for diagnosing muscle diseases.
  • Accurate diagnosis of myositis is important due to its established treatment options.
  • Differentiating myositis from other muscle pathologies presents a diagnostic challenge for pathologists.

Purpose of the Study:

  • To develop an artificial intelligence algorithm for the diagnosis of muscle biopsy.
  • To leverage deep convolutional neural networks for automated pathology slide analysis.
  • To enhance diagnostic accuracy and efficiency in muscle disease identification.

Main Methods:

  • Development of a deep convolutional neural network algorithm.
  • Training and testing the algorithm using 1,400 hematoxylin-and-eosin-stained muscle pathology slides.
  • Comparative analysis of algorithm performance against physician diagnoses.

Main Results:

  • The developed AI algorithm achieved high diagnostic performance.
  • The algorithm demonstrated superior sensitivity and specificity compared to human physicians.
  • Successful application of deep learning in analyzing histopathologic muscle biopsy images.

Conclusions:

  • Artificial intelligence holds significant potential for improving medical productivity in pathology.
  • The developed algorithm offers a promising tool for accurate and efficient muscle disease diagnosis.
  • AI-assisted diagnostics can support pathologists in challenging cases like myositis identification.