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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">MRP</journal-id><journal-title-group><journal-title>Medical Research and Practice</journal-title></journal-title-group><issn>2993-9690</issn><eissn>2993-9704</eissn><publisher><publisher-name>Art and Technology</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/MRP.11880</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>非啮齿类骨肉瘤动物模型的构建及AI在其的应用</title><url>https://artdesignp.com/journal/MRP/2/12/10.61369/MRP.11880</url><author>杨梦雪,唐雪峰</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>2</volume><issue>12</issue><history><date date-type="pub"><published-time>2024-12-20</published-time></date></history><abstract>骨肉瘤作为骨骼系统恶性程度最高的肿瘤之一，其临床治疗仍以手术联合化疗为主，但转移性患者的生存率长期未见突破。传统啮齿类模型虽广泛用于基础研究，但在模拟人类肿瘤微环境、转移机制及药物代谢等方面存在显著局限性。本文聚焦于鸡胚绒毛尿囊膜（CAM）、猪及犬等非啮齿类模型的转化潜力，并探讨人工智能（AI）技术在优化模型构建、数据分析及治疗开发中的协同作用。通过整合多组学数据、AI驱动的影像分析及智能药物筛选，这些模型为解析疾病分子机制及加速新疗法开发提供了多维平台，具有重要的临床转化价值。</abstract><keywords>骨肉瘤,非啮齿类动物模型,人工智能,骨肉瘤,转化医学</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]Moukengue B， Lallier M， Marchandet L， Baud'huin M， Verrecchia F， Ory B， Lamoureux F. 骨肉瘤的起源和治疗.癌症（巴塞尔）.2022 年 7 月 19 日;14(14):3503.doi：10.3390/cancers14143503。PMID：35884563;PMCID：PMC9322921.[2]费菲,曲莉莉.牛晓辉:肢体经典型骨肉瘤循证临床诊疗指南 中国医师协会骨科医师分会《骨肿瘤循证临床诊疗指南》编委会成员权威解读[J].中国医药科学,2015,5(12):1-3.[3]侯立刚,杨建义,马云山.基于监测、流行病学和最终结果数据库的骨肉瘤临床预测模型的构建[J].中华实验外科杂志,2021,38(12):2518-2522.[4]曹亮,张寿,邓建超,等.骨肉瘤化疗现状及新进展[J].海南医学,2015,26(16):2407-2409.[5] 喻帅克, 罗茂丽, 王连睿, 等. 基于数据挖掘的骨肉瘤动物模型应用分析[J].中国比较医学杂志,2023,33(11):55-62.[6]Zhang, YJ, Luo, Z, Sun, Y, et al. 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