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 Connective Tissues01:30

Classification of Connective Tissues

14.1K
The connective tissues have different properties and functions in the human body. They are broadly categorized into proper, supporting, or fluid connective tissues.
Connective Tissue Proper
Connective tissue proper is the most abundant class of connective tissues. As its name implies, it predominantly connects different tissues in the body. Depending on the cell types, ground substance, viscosity, and fiber types in the ECM, connective tissue proper is further categorized into loose and dense....
14.1K
Functional Classification of Joints01:09

Functional Classification of Joints

6.0K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
6.0K
Improving Translational Accuracy02:07

Improving Translational Accuracy

12.7K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
12.7K
Improving Translational Accuracy02:07

Improving Translational Accuracy

3.3K
3.3K
Classification of Leukocytes01:30

Classification of Leukocytes

4.3K
Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
4.3K
Force Classification01:22

Force Classification

2.0K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
2.0K

You might also read

Related Articles

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

Sort by
Same author

fAI-BRO: a multimodal AI decision-support system to address diagnostic delay in fibromyalgia syndrome.

RMD open·2026
Same author

Assessment of CDASI scoring by a multimodal large language model: a comparative study with expert assessors.

Rheumatology international·2026
Same author

Local LLM-based sentiment analysis of emotional patterns in complex-to-manage and treatment-resistant psoriatic arthritis.

Internal and emergency medicine·2026
Same author

Correction: Cazzato et al. Skin Mycetoma in an 11-Year-Old African Boy: Case Presentation with Emphasis on Histopathological Features and Differential Diagnosis. <i>Dermatopathology</i> 2021, <i>8</i>, 509-514.

Dermatopathology (Basel, Switzerland)·2026
Same author

The systemic immune-inflammation biomarkers in Sjögren's disease: associations with disease activity and extraglandular manifestations in a multicentric Italian cohort.

Internal and emergency medicine·2026
Same author

Integrating Large Language Models in Rheumatology: A Transformative Paradigm for Academia.

International journal of rheumatic diseases·2026

Related Experiment Video

Updated: Nov 23, 2025

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

7.2K

A convolutional neural network with transfer learning for automatic discrimination between low and high-grade

Vincenzo Venerito1, Orazio Angelini2,3, Gerardo Cazzato4

  • 1Department of Emergency and Organ Transplantations-Rheumatology Unit, University of Bari "Aldo Moro", Bari, Italy.

Internal and Emergency Medicine
|January 2, 2021
PubMed
Summary

Computer vision accurately grades synovitis in inflammatory arthritis patients using ultrasound-guided synovial tissue biopsy (USSB) images. This AI approach aids in personalizing treatment by quantifying inflammation, improving rheumatologist and pathologist workflows.

Keywords:
Convolutional neural networkMachine learningSynovitisUltrasound-guided synovial biopsy

Related Experiment Videos

Last Updated: Nov 23, 2025

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

7.2K

Area of Science:

  • Rheumatology
  • Digital Pathology
  • Artificial Intelligence

Background:

  • Ultrasound-guided synovial tissue biopsy (USSB) is key for personalizing inflammatory arthritis treatment.
  • Quantifying synovial tissue inflammation is crucial for effective therapeutic strategies.
  • Computer vision offers a potential tool for objective synovitis grading.

Purpose of the Study:

  • To investigate the utility of computer vision in discriminating low versus high-grade synovitis from synovial specimens.
  • To evaluate the performance of a convolutional neural network (CNN) for synovitis scoring.
  • To demonstrate the potential of AI in enhancing diagnostic workflows for inflammatory arthritis.

Main Methods:

  • A dataset of 150 H&E-stained synovial photomicrographs from USSB procedures was utilized.
  • Krenn's score was calculated for each slide to grade synovitis.
  • Transfer learning on a ResNet34 CNN was employed to classify synovitis as low (<5) or high (≥5).
  • Grad-Cam algorithm was used for model interpretability.

Main Results:

  • The CNN achieved 100% accuracy, precision, and recall in classifying synovitis in the test phase.
  • Cellularity in synovial lining and sublining layers was identified as the key predictor for CNN classification.
  • The model demonstrated robust performance on validation and test datasets.

Conclusions:

  • Computer vision, specifically using transfer learning with CNNs, is a viable method for accurately scoring synovitis.
  • This AI-driven approach shows promise for improving the efficiency and objectivity of synovitis assessment.
  • Integration into clinical practice could enhance collaboration between rheumatologists and pathologists for better patient management.