Akbarein Hesameddin, Taaghi Mohammad Hussein, Mohebbi Mahyar, Soufizadeh Parham
Department of Food Hygiene & Quality Control, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran.
Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran.
Vet Med Sci. 2025 May;11(3):e70315. doi: 10.1002/vms3.70315.
In recent years, artificial intelligence (AI) has brought about a significant transformation in healthcare, streamlining manual tasks and allowing professionals to focus on critical responsibilities while AI handles complex procedures. This shift is not limited to human healthcare; it extends to veterinary medicine as well, where AI's predictive analytics and diagnostic abilities are improving standards of animal care. Consequently, healthcare systems stand to gain notable advantages, such as enhanced accessibility, treatment efficacy, and optimized resource allocation, owing to the seamless integration of AI. This article presents a comprehensive review of the manifold applications of AI within the domain of veterinary science, categorizing them into four domains: clinical practice, biomedical research, public health, and administration. It also examines the primary machine learning algorithms used in relevant studies, highlighting emerging trends in the field. The research serves as a valuable resource for scholars, offering insights into current trends and serving as a starting point for those new to the field.
近年来,人工智能(AI)给医疗保健带来了重大变革,简化了手工任务,使专业人员能够专注于关键职责,同时由人工智能处理复杂程序。这种转变不仅限于人类医疗保健领域;它还延伸到了兽医学领域,在那里,人工智能的预测分析和诊断能力正在提高动物护理水平。因此,由于人工智能的无缝集成,医疗保健系统有望获得显著优势,如更高的可及性、治疗效果和优化的资源分配。本文全面综述了人工智能在兽医学领域的多种应用,并将其分为四个领域:临床实践、生物医学研究、公共卫生和管理。文章还研究了相关研究中使用的主要机器学习算法,突出了该领域的新兴趋势。这项研究为学者提供了宝贵的资源,深入洞察当前趋势,并为该领域的新手提供了一个起点。