Addressing the Data Scarcity Problem in Ecotoxicology via Small Data Machine Learning Methods

被引：0
|
作者：
Wang, Ying [1 ]
Dong, Jinchu [1 ]
Zhou, Yunchi [1 ]
Cheng, Yinghao [1 ,2 ]
Zhao, Xiaoli [3 ]
Peijnenburg, Willie J. G. M. [4 ,5 ]
Vijver, Martina G. [4 ]
Leung, Kenneth M. Y. [6 ,7 ]
Fan, Wenhong [1 ]
Wu, Fengchang [3 ]
机构：
[1] Beihang Univ, Sch Mat Sci & Engn, Beijing 100191, Peoples R China
[2] Nucl & Radiat Safety Ctr, Beijing 100082, Peoples R China
[3] Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China
[4] Leiden Univ, Inst Environm Sci, NL-2300 RA Leiden, Netherlands
[5] Natl Inst Publ Hlth & Environm, Ctr Safety Prod & Subst, NL-3720 BA Bilthoven, Netherlands
[6] City Univ Hong Kong, Dept Chem, State Key Lab Marine Pollut, Hong Kong 999077, Peoples R China
[7] City Univ Hong Kong, Sch Energy & Environm, Hong Kong 999077, Peoples R China
来源：
ENVIRONMENTAL SCIENCE & TECHNOLOGY | 2025年 / 59卷 / 12期
基金：
中国国家自然科学基金; 欧盟地平线“2020”; 北京市自然科学基金; 国家重点研发计划;
关键词：
ecotoxicity; small data machine learning (SDML); prediction; data augmentation; modeling workflow; artificial intelligence;
D O I：
10.1021/acs.est.5c00510
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
引用
收藏
页码：5867 / 5871
页数：5
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