Article(id=1317115200654914241, tenantId=1146029695717560320, journalId=1255847919539208197, issueId=1317115107243573307, articleNumber=null, orderNo=null, doi=10.13193/j.issn.1673-7717.2026.04.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791954334653, onlineDateStr=2026-10-14, pubDate=1775750400000, pubDateStr=2026-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791954334653, onlineIssueDateStr=2026-10-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791954334653, creator=13701087609, updateTime=1791954334653, updator=13701087609, issue=Issue{id=1317115107243573307, tenantId=1146029695717560320, journalId=1255847919539208197, year='2026', volume='44', issue='4', pageStart='1', pageEnd='258', issueExtLink='null', onlineDate='null', pubDate='1775750400000', pubDateStr='2026-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791954312382, creator='13701087609', updateTime=1791958738709, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1317133672680116252, tenantId=1146029695717560320, journalId=1255847919539208197, issueId=1317115107243573307, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1317133672680116253, tenantId=1146029695717560320, journalId=1255847919539208197, issueId=1317115107243573307, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=11, endPage=16, ext={EN=ArticleExt(id=1317115200927544002, articleId=1317115200654914241, tenantId=1146029695717560320, journalId=1255847919539208197, language=EN, title=Application and Research Progress of Digital Intelligence Technology in Traditional Chinese Medicine and Current Research Status, columnId=1256183375241535778, journalTitle=Chinese Archives of Traditional Chinese Medicine, columnName=Digital Traditional Chinese Medicine, runingTitle=null, highlight=null, articleAbstract=

Chinese medicines are collected, concocted and prepared under the guidance of traditional Chinese medicine theory, which explains the mechanism of drug action and guides clinical application, and is the crystallisation of the wisdom of the Chinese nation handed down for thousands of years. Due to the complexity of the mechanism of action of Chinese medicines, the development of the Chinese medicine industry is still in a relatively conservative stage. The rise of digital intelligence technology has brought new opportunities for the Chinese medicine industry and made significant progress. Digital intelligence technologies such as artificial intelligence, big data and intelligent senses are applied to traditional Chinese medicine identification, concoctions, preparations and quality evaluation, which have contributed to the vigorous development of the traditional Chinese medicine industry and driven the development of the traditional Chinese medicine industry. With the continuous progress and innovation of technology, the application of traditional Chinese medicine will be more scientific, efficient and environmentally friendly to better serve human health and make new contributions to the world health. On this basis, this paper discussed the application of digital intelligence technology in the field of traditional Chinese medicine and its development prospects, with a view to providing reference for the modern application of traditional Chinese medicine.

, authors=Mengyue WU¹, Xinzhen HUA², Junqing ZHU¹, Tianren XU¹, Huaixing KANG¹, Peng GAO¹, authorsList=Mengyue WU, Xinzhen HUA, Junqing ZHU, Tianren XU, Huaixing KANG, Peng GAO, authorCompany=null, correspAuthors=Huaixing KANG, Peng GAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1317115201317614275, articleId=1317115200654914241, tenantId=1146029695717560320, journalId=1255847919539208197, language=CN, title=数智化技术在中药领域的应用进展及研究现状分析, columnId=1256183387140776248, journalTitle=中华中医药学刊, columnName=数字中医中药, runingTitle=null, highlight=null, articleAbstract=

中药是在中国传统医药理论指导下采集、炮制、制剂，说明药物作用机理，指导临床应用的药物，是中华民族流传几千年的智慧结晶。由于中药作用机制的复杂性，中药产业的发展仍处于相对保守阶段，数智化技术的兴起，为中药行业带来新的机遇，并取得显著进展。人工智能、大数据以及智能感官等数智化技术应用于中药鉴定、炮制、制剂、质量评价等多个方面，促进了中医药行业的蓬勃发展，带动中药产业发展。随着技术的不断进步和创新，中药的应用将会更加科学、高效、环保，更好地服务于人类健康，并为世界卫生事业做出新的贡献。在此基础上，将数智化技术在中药领域的应用以及发展前景进行了论述，以期为中药的现代化应用提供参考。

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吴梦悦（1999-），女，河南商丘人，硕士在读，研究方向：中药制剂学。

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吴梦悦（1999-），女，河南商丘人，硕士在读，研究方向：中药制剂学。

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