Machine learning coupled with causal inference to identify COVID-19 related chemicals that pose a high concern to drinking water
文献类型：期刊论文
| 作者 | Han, Min1,2; Liang, Jun2,6; Jin, Biao1,3,7 ; Wang, Ziwei2; Wu, Wanlu2,5; Arp, Hans Peter H.4
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| 刊名 | ISCIENCE
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| 出版日期 | 2024-02-16 |
| 卷号 | 27期号:2页码:18 |
| DOI | 10.1016/j.isci.2024.109012 |
| 英文摘要 | Various synthetic substances were utilized in large quantities during the recent coronavirus pandemic, COVID-19. Some of these chemicals could potentially enter drinking water sources. Persistent, mobile, and toxic (PMT) substances have been recognized as a threat to drinking water resources. It has not yet been assessed how many COVID-19 related substances could be considered PMT substances. One reason is the lack of high -quality experimental data for the identification of PMT substances. To solve this problem, we applied a machine learning model to identify the PMT substances among COVID-19 related chemicals. The optimal model achieved an accuracy of 90.6% based on external test data. The model interpretation and causal inference indicated that our approach understood causation between PMT properties and molecular descriptors. Notably, the screening results showed that over 60% of the COVID-19 chemicals considered are candidate PMT substances, which should be prioritized to prevent undue pollution of water resources. |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001181386200001 |
| 源URL | [http://ir.gig.ac.cn/handle/344008/77342]  |
| 专题 | 有机地球化学国家重点实验室 |
| 通讯作者 | Jin, Biao |
| 作者单位 | 1.Guangdong Prov Key Lab Environm Protect & Resource, Guangzhou 510640, Peoples R China 2.Chinese Acad Sci, State Key Lab Organ Geochem, Guangzhou Inst Geochem, Guangzhou 510640, Peoples R China 3.CAS Ctr Excellence Deep Earth Sci, Guangzhou 510640, Peoples R China 4.Norwegian Univ Sci & Technol NTNU, NO-7491 Trondheim, Norway 5.Norwegian Geotech Inst NGI, POB 3930 Ullevaal Stad, N-0806 Oslo, Norway 6.South China Normal Univ, Sch Software, Foshan 528225, Peoples R China 7.Univ Chinese Acad Sci, Beijing 10069, Peoples R China |
| 推荐引用方式 GB/T 7714 | Han, Min,Liang, Jun,Jin, Biao,et al. Machine learning coupled with causal inference to identify COVID-19 related chemicals that pose a high concern to drinking water[J]. ISCIENCE,2024,27(2):18. |
| APA | Han, Min,Liang, Jun,Jin, Biao,Wang, Ziwei,Wu, Wanlu,&Arp, Hans Peter H..(2024).Machine learning coupled with causal inference to identify COVID-19 related chemicals that pose a high concern to drinking water.ISCIENCE,27(2),18. |
| MLA | Han, Min,et al."Machine learning coupled with causal inference to identify COVID-19 related chemicals that pose a high concern to drinking water".ISCIENCE 27.2(2024):18. |
入库方式： OAI收割
来源：广州地球化学研究所
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