Development of a Machine Learning Model to Estimate the Biotic Ligand Model-Based Predicted No-Effect Concentrations for Copper in Freshwater.

Chung, Jiwoong; Yoo, Geonwoo; Jo, Jae-Seong; Choi, Jinhee; Lee, Jong-Hyeon

Chung, Jiwoong; Yoo, Geonwoo; Jo, Jae-Seong; Choi, Jinhee; Lee, Jong-Hyeon.

Afiliação

Chung J; Environmental Health & Safety Research Institute, EH Research & Consulting, Incheon, Republic of Korea.
Yoo G; School of Environmental Engineering, Graduate School of Energy and Environmental Systems Engineering, University of Seoul, Seoul, Republic of Korea.
Jo JS; Environmental Health & Safety Research Institute, EH Research & Consulting, Incheon, Republic of Korea.
Choi J; Environmental Health & Safety Research Institute, EH Research & Consulting, Incheon, Republic of Korea.
Lee JH; School of Environmental Engineering, Graduate School of Energy and Environmental Systems Engineering, University of Seoul, Seoul, Republic of Korea.

Environ Toxicol Chem ; 42(10): 2271-2283, 2023 10.

Article em En | MEDLINE | ID: mdl-37377350

Assuntos

Cobre; Poluentes Químicos da Água; Cobre/toxicidade; Cobre/análise; Poluentes Químicos da Água/toxicidade; Poluentes Químicos da Água/análise; Ligantes; Água Doce; Qualidade da Água

Palavras-chave

Bioavailability; Biotic ligand model; Copper; Deep neural network; Ecological risk assessment

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Químicos da Água / Cobre Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google