Burti Silvia, Zotti Alessandro, Banzato Tommaso
Department of Animal Medicine, Production and Health, University of Padua, Padua, Italy.
Front Vet Sci. 2024 Aug 30;11:1437284. doi: 10.3389/fvets.2024.1437284. eCollection 2024.
The topic of diagnostic imaging error and the tools and strategies for error mitigation are poorly investigated in veterinary medicine. The increasing popularity of diagnostic imaging and the high demand for teleradiology make mitigating diagnostic imaging errors paramount in high-quality services. The different sources of error have been thoroughly investigated in human medicine, and the use of AI-based products is advocated as one of the most promising strategies for error mitigation. At present, AI is still an emerging technology in veterinary medicine and, as such, is raising increasing interest among in board-certified radiologists and general practitioners alike. In this perspective article, the role of AI in mitigating different types of errors, as classified in the human literature, is presented and discussed. Furthermore, some of the weaknesses specific to the veterinary world, such as the absence of a regulatory agency for admitting medical devices to the market, are also discussed.
在兽医学中，诊断成像错误以及减少错误的工具和策略方面的研究较少。诊断成像的日益普及和远程放射学的高需求使得减少诊断成像错误成为高质量服务的首要任务。在人类医学中，已经对不同的错误来源进行了深入研究，并且提倡使用基于人工智能的产品作为减少错误最有前景的策略之一。目前，人工智能在兽医学中仍然是一项新兴技术，因此，它在获得认证的放射科医生和普通从业者中都引起了越来越浓厚的兴趣。在这篇观点文章中，我们介绍并讨论了人工智能在减少人类文献中分类的不同类型错误方面的作用。此外，还讨论了兽医领域特有的一些弱点，例如缺乏医疗器械上市监管机构。
