Prediction of Smoking Behavior From Single Nucleotide Polymorphisms With Machine Learning Approaches.

Xu, Yi; Cao, Liyu; Zhao, Xinyi; Yao, Yinghao; Liu, Qiang; Zhang, Bin; Wang, Yan; Mao, Ying; Ma, Yunlong; Ma, Jennie Z; Payne, Thomas J; Li, Ming D; Li, Lanjuan

Xu, Yi; Cao, Liyu; Zhao, Xinyi; Yao, Yinghao; Liu, Qiang; Zhang, Bin; Wang, Yan; Mao, Ying; Ma, Yunlong; Ma, Jennie Z; Payne, Thomas J; Li, Ming D; Li, Lanjuan.

Afiliação

Xu Y; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Cao L; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Zhao X; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Yao Y; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Liu Q; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Zhang B; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Wang Y; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Mao Y; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Ma Y; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Ma JZ; Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States.
Payne TJ; Department of Otolaryngology and Communicative Sciences, University of Mississippi Medical Center, Jackson, MS, United States.
Li MD; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Chi
Li L; Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China.

Front Psychiatry ; 11: 416, 2020.

Article em En | MEDLINE | ID: mdl-32477189

Palavras-chave

feature selection; machine learning; prediction of smoking; single-nucleotide polymorphisms; smoking

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Psychiatry Ano de publicação: 2020 Tipo de documento: Article

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