Integrating non-target analysis and machine learning: a framework for contaminant source identification

Integrating non-target analysis and machine learning: a framework for contaminant source identification

Abstract Machine learning-based non-target analysis (ML-based NTA) faces the critical challenge of linking complex chemical signals to contamination sources. This review proposes a systematic framework of ML-assisted NTA for contaminant source identification, emphasizing the strategies and considera...

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Main Authors: Peng Liu, Ding Pan, Xin-Yi Jiao, Ji-Ning Liu, Peng-Hui Du, Peng-Cheng Li, Meng-Zhu Xue, Yan-Chao Jin, Cai-Shan Wang, Xue-Rong Wang, Ying-Zhi Ding, Guang-Ning Zhu, Jing-Hao Yang, Wen-Ze Wu, Lu-Feng Liang, Xin-Hui Liu, Li-Ping Li
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:npj Clean Water
Online Access:https://doi.org/10.1038/s41545-025-00504-z
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https://doi.org/10.1038/s41545-025-00504-z

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