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Commentary: Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies.

作者信息

Joslyn Steve K, Faulkner Josephine, Ma Doris, Appleby Ryan

机构信息

School of Veterinary and Life Sciences, Murdoch University, Perth, WA, Australia.

Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.

出版信息

Front Vet Sci. 2025 Jun 25;12:1615947. doi: 10.3389/fvets.2025.1615947. eCollection 2025.

Abstract
摘要

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本文引用的文献

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American College of Veterinary Radiology and European College of Veterinary Diagnostic Imaging position statement on artificial intelligence.
J Am Vet Med Assoc. 2025 Mar 19;263(6):773-776. doi: 10.2460/javma.25.01.0027. Print 2025 Jun 1.
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Veterinary radiologic error rate as determined by necropsy.
Vet Radiol Ultrasound. 2023 Jul;64(4):573-584. doi: 10.1111/vru.13259. Epub 2023 Jun 9.
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Evaluating artificial intelligence algorithms for use in veterinary radiology.
Vet Radiol Ultrasound. 2022 Dec;63 Suppl 1:871-879. doi: 10.1111/vru.13159.
8
Multireader Diagnostic Accuracy Imaging Studies: Fundamentals of Design and Analysis.
Radiology. 2022 Apr;303(1):26-34. doi: 10.1148/radiol.211593. Epub 2022 Feb 15.
9
Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers.
Radiol Artif Intell. 2020 Mar 25;2(2):e200029. doi: 10.1148/ryai.2020200029. eCollection 2020 Mar.

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