Appleby Ryan B, Difazio Matthew, Cassel Nicolette, Hennessey Ryan, Basran Parminder S
1Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.
2Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, KS.
J Am Vet Med Assoc. 2025 Mar 19;263(6):773-776. doi: 10.2460/javma.25.01.0027. Print 2025 Jun 1.
The American College of Veterinary Radiology (ACVR) and the European College of Veterinary Diagnostic Imaging (ECVDI) recognize the transformative potential of AI in veterinary diagnostic imaging and radiation oncology. This position statement outlines the guiding principles for the ethical development and integration of AI technologies to ensure patient safety and clinical effectiveness. Artificial intelligence systems must adhere to good machine learning practices, emphasizing transparency, error reporting, and the involvement of clinical experts throughout development. These tools should also include robust mechanisms for secure patient data handling and postimplementation monitoring. The position highlights the critical importance of maintaining a veterinarian in the loop, preferably a board-certified radiologist or radiation oncologist, to interpret AI outputs and safeguard diagnostic quality. Currently, no commercially available AI products for veterinary diagnostic imaging meet the required standards for transparency, validation, or safety. The ACVR and ECVDI advocate for rigorous peer-reviewed research, unbiased third-party evaluations, and interdisciplinary collaboration to establish evidence-based benchmarks for AI applications. Additionally, the statement calls for enhanced education on AI for veterinary professionals, from foundational training in curricula to continuing education for practitioners. Veterinarians are encouraged to disclose AI usage to pet owners and provide alternative diagnostic options as needed. Regulatory bodies should establish guidelines to prevent misuse and protect the profession and patients. The ACVR and ECVDI stress the need for a cautious, informed approach to AI adoption, ensuring these technologies augment, rather than compromise, veterinary care.
美国兽医放射学会（ACVR）和欧洲兽医诊断影像学会（ECVDI）认识到人工智能在兽医诊断影像和放射肿瘤学方面的变革潜力。本立场声明概述了人工智能技术道德发展与整合的指导原则，以确保患者安全和临床有效性。人工智能系统必须遵循良好的机器学习规范，强调透明度、错误报告以及在整个开发过程中临床专家的参与。这些工具还应包括用于安全处理患者数据和实施后监测的强大机制。该立场强调了让兽医，最好是获得委员会认证的放射科医生或放射肿瘤学家参与其中以解读人工智能输出结果并保障诊断质量的至关重要性。目前，尚无用于兽医诊断影像的市售人工智能产品符合透明度、验证或安全方面的要求标准。ACVR和ECVDI倡导进行严格的同行评审研究、无偏见的第三方评估以及跨学科合作，以建立基于证据的人工智能应用基准。此外，该声明呼吁加强对兽医专业人员的人工智能教育，从课程中的基础培训到从业者的继续教育。鼓励兽医向宠物主人披露人工智能的使用情况，并根据需要提供其他诊断选项。监管机构应制定指导方针，以防止滥用并保护该行业和患者。ACVR和ECVDI强调需要以谨慎、明智的方式采用人工智能，确保这些技术增强而非损害兽医护理。
