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Using Environmental Mixture Exposure-Triggered Biological Knowledge-Driven Machine Learning to Predict Early Pregnancy Loss

Year: 2025

Type: article

Study design: Observational Study

Source: Environmental Science & Technology

DOI: 10.1021/acs.est.5c05389

Authors: Mengyuan Ren, Tianxiang Wu, Han Zhang, Shuo Yang, Lu Zhao, Lili Zhuang, Qun Lu, Xikun Han, Bo Pan, Tiantian Li, Jingchuan Xue, Yuanchen Chen, Michael S. Bloom, Mingliang Fang, Bin Wang

Institutions: Peking University, National Health and Family Planning Commission, Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Capital Medical University, Beijing Chao-Yang Hospital, Capital Medical University, Peking University People's Hospital, Kunming University of Science and Technology, Chinese Center For Disease Control and Prevention, Guangdong University of Technology, Zhejiang University of Technology, George Mason University, Fudan University

Language: English

Topic: Effects and risks of endocrine disrupting chemicals

Subfield: Health, Toxicology and Mutagenesis

Field: Environmental Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Natural Science Foundation of China, Chinese Academy of Sciences, National Key Research and Development Program of China

Awards: G3178855126, G5151698958, G5537652955, G6484551897, G6947989268

OpenAlex ID: W4413822018

FWCI: 6.018

Cites: 48

Cited by: 15

Related to: 10