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In this paper, we discuss the impact of the Covid-19 pandemic on alcoholconsumption habit changes among healthcare workers in the United States. Weutilize multiple supervised and unsupervised machine learning methods andmodels such as Decision Trees, Logistic Regression, Naive Bayes classifier,k-Nearest Neighbors, Support Vector Machines, Multilayer perceptron, XGBoost,CatBoost, LightGBM, Chi-Squared Test and mutual information method on a mentalhealth survey data obtained from the University of Michigan Inter-UniversityConsortium for Political and Social Research to find out relationships betweenCOVID-19 related negative effects and alcohol consumption habit changes amonghealthcare workers. Our findings suggest that COVID-19-related school closures,COVID-19-related work schedule changes and COVID-related news exposure may leadto an increase in alcohol use among healthcare workers in the United States.

A Machine Learning Analysis of Impact of the Covid-19 Pandemic on Alcohol Consumption Habit Changes Among Healthcare Workers in the U.S