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

You might also read

Related Articles

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

Sort by
Same author

Preoperative Risk Evaluation for Cancer Treatment (PREdiCT): protocol for an international cohort study evaluating a trimodal screening tool to predict outcomes following gastrointestinal cancer surgery.

BMJ open·2026
Same author

An outbreak of Salmonella Waycross related to sandpit contamination in a Gold Coast childcare centre, Queensland, Australia, 2024.

Communicable diseases intelligence (2018)·2026
Same author

A modified Delphi consensus on tenosynovial giant cell tumour and giant cell tumour of bone : a report from the Birmingham Orthopaedic Oncology Meeting (BOOM).

The bone & joint journal·2026
Same author

Complications of PI to PIII hemipelvic resections for intermediate and malignant tumours : a systematic review and meta-analysis.

Bone & joint open·2026
Same author

Economic impact of preoperative frailty in patients undergoing cytoreductive surgery.

Journal of geriatric oncology·2026
Same author

Practice patterns of Urological Society of Australia and New Zealand urologists regarding pelvic lymph node dissection in prostate cancer surgery.

Prostate international·2026
Same journal

Ultrasonographic Assessment of the Lungs in Asiatic Elephants (Elephas maximus).

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association·2026
Same journal

The Addition of a 3D Balanced Steady-State Free Precession Pulse Sequence Improves Magnetic Resonance Imaging Identification of Certain Canine Cranial Nerves.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association·2026
Same journal

Computed Tomographic Features of a Histopathologically Confirmed Nasal Dermoid Sinus in a Dog.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association·2026
Same journal

Thoracic Duct Branch Identification Is Comparable Between T2-W 3D Fat-Suppressed Magnetic Resonance Imaging and Computed Tomography Lymphangiography in Normal Dogs.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association·2026
Same journal

Biliary Peritonitis Secondary to Proximal Duodenal Perforation in a Cat.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association·2026
Same journal

Quantitative Parameters of Contrast-Enhanced Ultrasonography (CEUS) Monitoring Ovarian Hemodynamics in Rats.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association·2026
See all related articles

Related Experiment Video

Updated: Aug 17, 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

6.9K

Evaluating artificial intelligence algorithms for use in veterinary radiology.

Steve Joslyn1, Kate Alexander2

  • 1ACVR/ECVDI AI Education and Development Committee, Vedi, Perth, Western Australia, Australia.

Veterinary Radiology & Ultrasound : the Official Journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
|December 14, 2022
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) offers benefits in veterinary radiology but lacks regulation. Veterinarians must evaluate AI tools for clinical use, as discussed in this article.

Keywords:
algorithmartificial intelligenceevaluationradiologyveterinary

More Related Videos

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

938
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:30

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

164

Related Experiment Videos

Last Updated: Aug 17, 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

6.9K
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

938
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:30

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

164

Area of Science:

  • Veterinary medicine
  • Medical imaging
  • Artificial intelligence

Background:

  • Artificial intelligence is gaining traction in veterinary radiology for tasks like abnormality detection and automated measurements.
  • Unlike human medicine, veterinary radiology lacks formal regulation and validation for AI algorithms.
  • Veterinarians must exercise professional judgment when integrating AI into clinical practice.

Purpose of the Study:

  • To discuss the benefits and challenges associated with developing clinically useful and diagnostically accurate AI algorithms for veterinary radiology.
  • To address key considerations for initiating AI research projects in veterinary radiology.
  • To propose a framework for assessing AI algorithms in veterinary radiology for both research and clinical settings.

Main Methods:

  • Literature review and expert discussion on AI development and validation in veterinary radiology.
  • Analysis of current regulatory landscapes and their implications for veterinary AI.
  • Conceptualization of a framework for AI algorithm assessment.

Main Results:

  • Identified significant benefits of AI in enhancing diagnostic accuracy and efficiency in veterinary radiology.
  • Highlighted the critical challenges, including the absence of standardized validation and regulatory oversight.
  • Presented a proposed framework to guide veterinarians in evaluating AI tools.

Conclusions:

  • Veterinary radiology requires a structured approach to AI adoption due to the lack of formal regulation.
  • The proposed framework can assist veterinarians in making informed decisions about incorporating AI into their practice.
  • Further research and development are needed to ensure the safe and effective use of AI in veterinary diagnostics.