Current applications and future impact of machine learning in emerging contaminants: A review-Reference-Cited by-同舟云学术

Current applications and future impact of machine learning in emerging contaminants: A review

Published:2023-03-23 Issue:20 Volume:53 Page:1817-1835
ISSN:1064-3389
Container-title:Critical Reviews in Environmental Science and Technology
language:en
Short-container-title:Critical Reviews in Environmental Science and Technology

Author:

Lei Lang¹,Pang Ruirui¹,Han Zhibang¹,Wu Dong¹²³⁴,Xie Bing¹²³⁴,Su Yinglong¹²³⁴

Affiliation:

1. Shanghai Engineering Research Center of Biotransformation of Organic Solid Waste, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China

2. Engineering Research Center for Nanophotonics & Advanced Instrument, Ministry of Education, East China Normal University, Shanghai, China

3. Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai, China

4. Shanghai Institute of Pollution Control and Ecological Security, Shanghai, China

Funder

Natural Science Foundation of Shanghai

Shanghai Engineering Research Center of Biotransformation of Organic Solid Waste

Open Research Fund of State Key Laboratory of Estuarine and Coastal Research

Natural Science Foundation Project of CQ

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Subject

Pollution,Waste Management and Disposal,Water Science and Technology,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10643389.2023.2190313

Reference108 articles.

1. Estimation of tetracycline antibiotic photodegradation from wastewater by heterogeneous metal-organic frameworks photocatalysts

2. Horizontal Gene Exchange in Environmental Microbiota

3. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data

4. Machine learning predicts the functional composition of the protein corona and the cellular recognition of nanoparticles

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