Work

A rapid approach with machine learning for quantifying the relative burden of antimicrobial resistance in natural aquatic environments

Year: 2024

Type: article

Source: Water Research

DOI: 10.1016/j.watres.2024.122079

Authors: Peng Jiang, Shuyi Sun, Shin Giek Goh, Xuneng Tong, Yihan Chen, Kaifeng Yu, Yiliang He, Karina Yew-Hoong Gin

Institutions: National University of Singapore, Sichuan University, NUS Environmental Research Institute, Hefei University of Technology, Shanghai Jiao Tong University

Language: English

Topic: Pharmaceutical and Antibiotic Environmental Impacts

Subfield: Pollution

Field: Environmental Science

Domain: Physical Sciences

SDGs: Clean water and sanitation, Good health and well-being

Open Access status: closed

Funders: National Research Foundation, National University of Singapore, National Research Foundation Singapore, National Natural Science Foundation of China, National Research Foundation of Korea, Sichuan University, Natural Science Foundation of Sichuan Province

Awards: G3485802943, G4322283638, G4582146073, G6755309902

OpenAlex ID: W4400487528

FWCI: 1.478

Cites: 60

Cited by: 16

Related to: 10