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Artificial intelligence 101 for veterinary diagnostic imaging.

Adrien-Maxence Hespel1, Youshan Zhang2, Parminder S Basran2

  • 1Department of Small Animal Clinical Sciences, University of Tennessee, Knoxville, Tennessee, USA.

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) in veterinary radiology is expanding. This article explains AI, machine learning, and natural language processing (NLP) for veterinary professionals to understand AI research.

Keywords:
artificial intelligenceconvolutional neural networkmachine learningnatural language processingveterinary radiologist

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Area of Science:

  • Veterinary medicine
  • Medical imaging
  • Artificial intelligence

Background:

  • Artificial intelligence (AI) is increasingly used in veterinary and human medical imaging.
  • Understanding AI is crucial for interpreting AI-focused research in veterinary radiology.

Purpose of the Study:

  • To provide veterinarians and radiologists with foundational knowledge of AI in medical imaging.
  • To explain machine learning, deep learning, and natural language processing (NLP) for AI applications in veterinary radiology.

Main Methods:

  • Comparison of common machine learning methods in medical image analysis.
  • Detailed explanation of convolutional neural networks (CNNs) for deep learning models.
  • Introduction to natural language processing (NLP) and its role in creating training data.

Main Results:

  • AI, particularly CNNs, offers powerful tools for image classification and regression.
  • NLP can streamline the creation of essential "truth-data" for training AI systems.
  • The study provides a comprehensive overview of AI concepts relevant to veterinary radiology.

Conclusions:

  • Veterinarians and radiologists need a solid understanding of AI principles to engage with current research.
  • AI technologies like CNNs and NLP are transforming medical image analysis and data management.
  • This publication equips veterinary professionals to comprehend and utilize AI in diagnostic radiology and radiation oncology.