Prediction of Bipolar Disorder Using Machine Learning Techniques

Abstract

bipolar disorder may be an advanced disorder that affects variant individuals across the world. We assume that with the utilization of huge information with machine learning we will facilitate every patient as well as doctors to perform a much better designation of this sickness. Paper aims to use different Machine learning algorithms to predict the variants of bipolar disorder. The prediction model would help the psychiatrists fordiagnosing whether the patients are having a depression or mania episode, or staying in an exceedingly euthymic state. It also aims at developing a prophetic model with an appropriate level of confidence, it's essential to own each associate understanding of the information that's getting used and also thetheory relating to every algorithmic rule that's applied, similarly as having enough information for the algorithms to figure with.