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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Commentary: Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies.
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本文引用的文献
1
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.
2
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Front Vet Sci. 2025 Feb 21;12:1502790. doi: 10.3389/fvets.2025.1502790. eCollection 2025.
3
An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs.
Sci Rep. 2023 Oct 9;13(1):17024. doi: 10.1038/s41598-023-44089-4.
4
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.
5
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Vet Radiol Ultrasound. 2022 Dec;63 Suppl 1(Suppl 1):840-850. doi: 10.1111/vru.13171.
6
Evaluating artificial intelligence algorithms for use in veterinary radiology.
Vet Radiol Ultrasound. 2022 Dec;63 Suppl 1:871-879. doi: 10.1111/vru.13159.
7
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Stat Med. 2022 Jul 20;41(16):3022-3038. doi: 10.1002/sim.9400. Epub 2022 Apr 5.
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
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Radiol Artif Intell. 2020 Mar 25;2(2):e200029. doi: 10.1148/ryai.2020200029. eCollection 2020 Mar.
10
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.
BMJ. 2020 Mar 25;368:m689. doi: 10.1136/bmj.m689.
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