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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 Design</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/MRP.2025100022</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>基因组学、神经影像学与机器学习在癫痫精准治疗中的研究进展与应用整合</title><url>https://artdesignp.com/journal/MRP/3/10/10.61369/MRP.2025100022</url><author>孙梦阳,王艳玲</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>3</volume><issue>10</issue><history><date date-type="pub"><published-time>2025-10-20</published-time></date></history><abstract>癫痫是一种复杂的慢性神经系统疾病，其传统诊疗模式在病因诊断与治疗策略上面临挑战。随着基因组学、神经影像学与机器学习等技术的发展，癫痫的精准治疗已成为研究前沿。多模态数据整合能系统揭示癫痫从基因到表型的完整病理生理过程，为实现精准诊断、预后预测及动态治疗奠定基础。本文通过回顾国内外相关文献，分别阐述上述三项技术在癫痫精准治疗中的最新应用及整合策略，探讨其构建个体化治疗体系的潜力与路径。</abstract><keywords>癫痫,精准治疗,多模态数据整合,机器学习</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>&amp;nbsp;[1]World Health Organization. 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