A Machine Learning Approach to Identification of Unhealthy Drinking

Journal of the American Board of Family Medicine: JABFM

article

Levi N. Bonnell¹  Benjamin Littenberg¹  Safwan R. Wshah²  Gail L. Rose¹ 

[1] From University of Vermont College of Medicine;University of Vermont, College of Engineering and Mathematical Sciences

关键词: Alcohol Drinking;    Alcoholism;    Area Under Curve;    Clinical Decision Rules;    Decision Trees;    Logistic Models;    Machine Learning;    Neural Networks (Computer);    Nutrition Surveys;    Support Vector Machine;   

DOI  :  10.3122/jabfm.2020.03.190421

学科分类：过敏症与临床免疫学

来源: The American Board of Family Medicine

【 摘 要 】

Introduction: Unhealthy drinking is prevalent in the United States, and yet it is underidentified and undertreated. Identifying unhealthy drinkers can be time-consuming and uncomfortable for primary care providers. An automated rule for identification would focus attention on patients most likely to need care and, therefore, increase efficiency and effectiveness. The objective of this study was to build a clinical prediction tool for unhealthy drinking based on routinely available demographic and laboratory data.

【 授权许可】

CC BY