1Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY.
2Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.
J Am Vet Med Assoc. 2024 Apr 10;262(8):1090-1098. doi: 10.2460/javma.24.01.0027. Print 2024 Aug 1.
This report describes a comprehensive framework for applying artificial intelligence (AI) in veterinary medicine. Our framework draws on existing research on AI implementation in human medicine and addresses the challenges of limited technology expertise and the need for scalability. The critical components of this framework include assembling a diverse team of experts in AI, promoting a foundational understanding of AI among veterinary professionals, identifying relevant use cases and objectives, ensuring data quality and availability, creating an effective implementation plan, providing team training, fostering collaboration, considering ethical and legal obligations, integrating AI into existing workflows, monitoring and evaluating performance, managing change effectively, and staying up-to-date with technological advancements. Incorporating AI into veterinary medicine requires addressing unique ethical and legal considerations, including data privacy, owner consent, and the impact of AI outputs on decision-making. Effective change management principles aid in avoiding disruptions and building trust in AI technology. Furthermore, continuous evaluation of AI's relevance in veterinary practice ensures that the benefits of AI translate into meaningful improvements in patient care.
本报告描述了在兽医医学中应用人工智能 (AI) 的综合框架。我们的框架借鉴了人类医学中 AI 实施的现有研究，并解决了技术专业知识有限和可扩展性需求的挑战。该框架的关键组成部分包括：组建一个由 AI 专家组成的多元化团队，在兽医专业人员中推广对 AI 的基本了解，确定相关用例和目标，确保数据的质量和可用性，创建有效的实施计划，提供团队培训，促进协作，考虑伦理和法律义务，将 AI 融入现有工作流程，监测和评估性能，有效地管理变更，以及跟上技术进步。将 AI 纳入兽医医学需要解决独特的伦理和法律问题，包括数据隐私、所有者同意以及 AI 输出对决策的影响。有效的变更管理原则有助于避免干扰并建立对 AI 技术的信任。此外，持续评估 AI 在兽医实践中的相关性，确保 AI 的优势转化为患者护理的有意义改进。
