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Advances and applications of machine learning and deep learning in environmental ecology and health.
Cui, Shixuan; Gao, Yuchen; Huang, Yizhou; Shen, Lilai; Zhao, Qiming; Pan, Yaru; Zhuang, Shulin.
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  • Cui S; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China; Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China.
  • Gao Y; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Huang Y; Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China.
  • Shen L; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Zhao Q; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Pan Y; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Zhuang S; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China; Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China. Electronic address: shulin@zju.edu
Environ Pollut ; 335: 122358, 2023 Oct 15.
Article en En | MEDLINE | ID: mdl-37567408
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido