Choudhary Om Prakash, Infant Shofia Saghya, As Vickram, Chopra Hitesh, Manuta Nicoleta
Department of Veterinary Anatomy, College of Veterinary Science, Guru Angad Dev Veterinary and Animal Sciences University, Rampura Phul, Bathinda, Punjab 151103, India.
Department of Biotechnology, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India.
Ann Anat. 2025 Feb;258:152366. doi: 10.1016/j.aanat.2024.152366. Epub 2024 Dec 3.
Artificial intelligence (AI) is revolutionizing veterinary medicine, particularly in the domain of veterinary anatomy. At present, there is no existing review article in the literature that examines the prospects and challenges associated with the use of AI in animal anatomy education.
Narrative review.
This review article explores the prospects and drawbacks of AI applications in veterinary anatomy. Anatomy and AI-powered diagnostic systems enhance clinical examination, diagnosis, and treatment by analyzing vast datasets, improving accuracy, and detecting subtle anomalies.
We reviewed and analyzed recent literature on AI applications in veterinary anatomy education, emphasizing their potential, limitations, and future directions..
In veterinary anatomy education, AI integrates advanced tools like three-dimensional (3D) models, virtual reality (VR), and augmented reality (AR), offering dynamic and interactive learning experiences to students as well as the faculty of veterinary institutions across the globe. Despite these advantages, AI faces challenges such as the need for extensive, high-quality data, potential biases, and issues with algorithmic transparency. Additionally, virtual dissection and educational tools may impact hands-on learning and ethical and legal concerns regarding data privacy must be addressed. Balancing AI integration with traditional skills and addressing these challenges will maximize AI's benefits in veterinary anatomy and ensure comprehensive veterinary care.
人工智能(AI)正在彻底改变兽医学,尤其是在兽医解剖学领域。目前,文献中尚无现有的综述文章探讨在动物解剖学教育中使用人工智能的前景和挑战。
叙述性综述。
本文综述探讨人工智能在兽医解剖学中的应用前景和弊端。解剖学和人工智能驱动的诊断系统通过分析大量数据集、提高准确性和检测细微异常来加强临床检查、诊断和治疗。
我们回顾并分析了近期关于人工智能在兽医解剖学教育中应用的文献,重点关注其潜力、局限性和未来发展方向。
在兽医解剖学教育中,人工智能整合了三维(3D)模型、虚拟现实(VR)和增强现实(AR)等先进工具,为全球兽医机构的学生和教师提供了动态且互动的学习体验。尽管有这些优势,但人工智能面临诸多挑战,如需要大量高质量数据、潜在偏差以及算法透明度问题。此外,虚拟解剖和教育工具可能会影响实践操作学习,必须解决数据隐私方面的伦理和法律问题。在将人工智能整合与传统技能之间取得平衡并应对这些挑战,将使人工智能在兽医解剖学中的益处最大化,并确保全面的兽医护理。