Machine Learning Algorithm for Predicting Mood Disturbances

Abstract

One of the complicated diseases that pose the biggest global public health challenges are Mood Disturbances. Mood Disturbances can also be referred to as mood disorders or anticipating mood disturbance. They have an impact on both sexes, as well as individuals of all ages, from infants to the elderly. Mood Disturbances disorders can have a variety of negative effects on a person's health and wellbeing. They are also responsible for a wide range of psycho-social symptoms like low mood, social withdrawal, decreased workplace productivity, suicidal ideation or attempt, difficulty concentrating. The purpose of this study is to investigate the application of machine learning algorithms in predicting the occurrence of Mood Disturbances in individuals. This study showed a viable and reliable model for predicting Mood Disturbances symptoms. The experiment's findings showed that the predictive model, with precision of 97%, recall rate of 79%, f1-score of 87%, and accuracy of 88%, was effective when compared to some other existing models on Mood Disturbances prediction