Artificial Intelligent System for Mental Health Prediction of Information Technology (IT) Workers

Abstract

Much of today's academic research implies that Artificial Intelligence (AI) is a technology that can be used in a wide range of applications. Engineering, social sciences, administration, and medicine are only a few examples. The purpose of this paper is to provide an overview of the application of artificial intelligence on the mental health analysis of information technology workers. The aim of this study is to figure out how accurate artificial intelligence systems are at predicting mental health. In the examination of a public data set containing 287 samples, several linear regression techniques such as Random Forest, XGBoost, Logistic Regression, and Artificial Neural Network are applied, in order to achieve predictive accuracy and precision of each algorithm. The proposed method indicates that Random Forest algorithm is the most effective in analyzing and predicting the risk of developing mental health problems. With a percentage precision of 90.85 and a percentage of accuracy of 92.33, or a percentage of sensitivity of 94.56 and a percentage of specificity of 90.00.