[关键词]
[摘要]
中药古法煎煮一直作为获得中药汤剂的首选方法，随着数字化信息高速发展，古法煎煮工艺繁杂、耗费人工、自煎差异大等问题突出。现代中药煎煮机的引进，很大程度上提高了煎煮效率和服药的便捷性，并且随着现代化中药智能煎煮不断地发展研究，中药煎煮也不断走向智能化、集约化、规范化。由于目前中药煎煮与数字化的中药古法煎煮理论没有建立数字化的联系，导致中药煎煮存在“智能不足、缺乏自我决策”等问题，因此建立中药煎煮与古法煎煮理论的数字化、智能化联系，推进中药古法煎煮向智能化、数字化转型升级是大势所趋。数据与知识是实现数字化智能发展的驱动力，因此针对数字化中药古法煎煮存在的瓶颈，结合过程分析（process analysis technology，PAT）、人工智能、数据库、物联网等高新技术，展望数字化古法煎煮的未来发展趋势，以期为中药古法煎煮进一步开发研究提供参考。
[Key word]
[Abstract]
Ancient decoction of traditional Chinese medicine (TCM) has always been the preferred method to obtain TCM decoction. With the rapid development of digital information, the problems of complicated ancient decoction process, labor-consuming and large difference in self-decoction are prominent. The introduction of modern Chinese medicine decoction machine has greatly improved the efficiency of decoction and the convenience of taking medicine. With the continuous development and research of modern Chinese medicine intelligent decoction, TCM decoction is also constantly moving towards intelligence, intensification and standardization. At present, there is no digital connection between TCM decoction and digital ancient TCM decoction theory, which leads to the problems of “lack of intelligence and lack of self-decision-making” in TCM decoction. Therefore, it is the general trend to establish the digital and intelligent connection between TCM decoction and ancient TCM decoction theory, and to promote the intelligent and digital transformation and upgrading of ancient TCM decoction. Data and knowledge are the driving forces for the development of digital intelligence. Therefore, in view of the bottleneck of digital ancient TCM decoction, combined with process analysis technology (PAT), artificial intelligence, database, internet of things and other high-tech, the future development trend of digital ancient TCM decoction is prospected, in order to provide reference for the further development and research of ancient TCM decoction.
[中图分类号]
R283
[基金项目]
中央引导地方科技发展资金项目（2022ZDD03085）;江西省学位与研究生教育教学改革项目（JXYJG-2022-152）;江西省中药绿色制造技术创新中心（20222BCD43008）;国家级高层次人才支持计划;江西省高水平本科教学团队（赣教高办函[2022]10号）
