中国药科大学学报2024，Vol.55Issue(3)：316-325,10.DOI:10.11665/j.issn.1000-5048.2023113003
机器学习在合成大麻素识别鉴定中的应用进展
Advances in the application of machine learning in the identification and authentication of synthetic cannabinoids
摘要
Abstract
Synthetic cannabinoids(SCs)are synthetic psychoactive substances that can pose a public health risk.The SCs are structurally variable and susceptible to structural modification.The rapid emergence of structurally unknown synthetic cannabinoids has led to new challenges in their identification.In recent years,machine learning has made great progress and has been widely applied to other fields,providing new strategies for the identification of unknown synthetic cannabinoids and the inference of possible sources.This paper describes the principles of commonly used machine learning methods and the application of machine learning techniques to mass spectrometry,Raman spectroscopy,metabolomics and quantitative conformational relationships of synthetic cannabinoids,aiming to provide new ideas for the identification of unknown synthetic cannabinoids.关键词
合成大麻素/机器学习/非靶向筛查Key words
synthetic cannabinoids/machine learning/non-targeted screening分类
信息技术与安全科学引用本文复制引用
许情,吕敏,邓虹霄,胡驰,向平,陈航..机器学习在合成大麻素识别鉴定中的应用进展[J].中国药科大学学报,2024,55(3):316-325,10.基金项目
This study was supported by the National Key Research and Development Program of China(No.2022YFC3300903),the Social Welfare Research Projects of Centralized Research Institutes(No.GY2022D-1),and the Project of Shanghai Key Laboratory of Forensic Medicine(No.21DZ2270800) 国家重点研发计划项目(No.2022YFC3300903) （No.2022YFC3300903）
中央级科研院所社会公益研究专项(No.GY2022D-1) （No.GY2022D-1）
上海市法医学重点实验室资助项目(No.21DZ2270800) （No.21DZ2270800）
