A predictive model for bipolar disorder episodes

Abstract

Bipolar disorder is one of the critical condition of mental illness which possess various challenges in order to determine it with higher accuracy. This form of mental illness is connected with occurrences of varied episodes of mood transition which could eventually range from lower intensity (depression) to higher intensity (manic). Although, currently there is no specific findings to state the reason or cause of this form of mental illness, however, such form of illness is found to be triggered by various attributes e.g. changed structure and chemistry of brain, environment, and genetics. The occurrence of higher intensity of this illness is witnessed with a frequently occurring symptoms e.g. detachment with real world, reduced sleep, extensive energy, etc. while the occurrence of lower intensity of this illness is characterized by loss of interest in normal activities, reduced interest and motivation, reduced state of energy. The extent of the occurrence of the mood episodes resides ranging from short duration (days) to long duration (months). Apart from this, such episodes are also connected with the provoking internal suicidal thoughts . Another complexity towards the treatment is to correctly determining the actual state of the bipolar disorder, another complication is towards the treatment. Usually such treatment and therapies are of extensive duration ranging from couple of years to lifetime. Such treatments are carried out by less by medication and more by psychotherapies.