Submission
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Abstract ID：
1791
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Title：
Exploring the correlations between physicochemical parameters and the presence of opportunistic pathogens in drinking water using a machine learning approach
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Author：
Hyeok Kim1, †, Juliana Marks2, Hyun-Suk Oh1,3, Rabin Bhattarai4, and Helen Nguyen*2
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Institute：
1Department of Environmental Engineering, Seoul National University of Science and Technology, 232, Gongneung-ro, Nowon-gu, Seoul, 01811, Republic of Korea 2Department of Civil and Environmental Engineering, The Grainger College of Engineering, University of Illinois at Urbana-Champaign 3 Institute of Environmental Technology, Seoul National University of Science & Technology, Seoul 01811, Republic of Korea 4Department of Agricultural and Biological Engineering, The Grainger College of Engineering & College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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Keywords：
Legionella spp., water quality parameter, machine learning
