机器学习算法在中药活性成分筛选中的应用OA
Application of machine learning algorithms in screening of active components in Chinese materia medica
中药作为复杂的化学体系,其活性成分筛选长期面临成分多样性高、作用机制不明等挑战.近年来,机器学习算法技术的介入为中药现代化研究提供了新范式.系统梳理机器学习算法的分类并探讨其在中药活性成分筛选中的应用场景、技术挑战与优化策略.
Chinese materia medica(CMM),as a complex chemical system,has long faced challenges in active components screening,such as the high compositional diversity and unclear mechanisms of action.In recent years,the integration of machine learning algorithms has provided a new paradigm for the modernization of CMM research.This paper systematically reviews the classification of machine learning algorithms and explores their application scenarios,technical challenges,and optimization strategies in the screening of active components from CMM.
张能仪;李园园;王天明
上海中医药大学中药学院(上海 201203)上海中医药大学中药学院(上海 201203)上海中医药大学中药学院(上海 201203)
人工智能中药活性成分机器学习大语言模型算法
artificial intelligenceChinese materia medicaactive componentsmachine learninglarge language modelsalgorithms
《上海中医药杂志》 2026 (2)
1-10,10
国家自然科学基金项目(82404823)上海中医药大学科技发展项目(23KFL043)
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