Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan, L Wang, M Vanyukov… - Drug and alcohol …, 2020 - Elsevier
Background This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …
被引用次数：27 相关文章

Analysis of substance use and its outcomes by machine learning: II. derivation and prediction of the trajectory of substance use severity.

Z Hu, Y Jing, Y Xue, P Fan, L Wang, M Vanyukov… - 2020 - cabidigitallibrary.org
Background: This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …

Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan, L Wang… - Drug and alcohol …, 2019 - safetylit.org
BACKGROUND: This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …
[HTML] nih.gov

[HTML][HTML] Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan, L Wang… - Drug and alcohol …, 2020 - ncbi.nlm.nih.gov
Background: This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …

Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan… - Drug and …, 2020 - utsouthwestern.elsevierpure.com
Background: This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …

Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan, L Wang… - Drug and alcohol …, 2020 - pubmed.ncbi.nlm.nih.gov
Background This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …

Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity.

Z Hu, Y Jing, Y Xue, P Fan, L Wang… - Drug and Alcohol …, 2019 - europepmc.org
Background This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …
[PDF] academia.edu

[PDF][PDF] Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan, L Wang, M Vanyukov… - 2019 - academia.edu
Background: This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …

Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity

Z Hu, Y Jing, Y Xue, P Fan, L Wang… - Drug and alcohol …, 2019 - safetylit.org
BACKGROUND: This longitudinal study explored the utility of machine learning (ML)
methodology in predicting the trajectory of severity of substance use from childhood to thirty …