Computational Techniques in Prognostic and Data Modelling of Mentally Ill Patients with Special Emphasis on Post-COVID-19 Scenario

Abstract

Mental health illnesses and psychological disorders have been on the rise for the past few years. As per WHO (2020) [1], 1 billion people in the world suffer from a mental disorder. The current COVID-19 situation contributed significantly to a rise in the number of patients registering under severe mental illnesses. These disorders, if detected early, can be controlled and treated well. The detection can be done using predictive models, computational and data analytical tools. This chapter focuses on understanding the role of various such models and tools in detection as well as treatment of the concerned mental conditions. The authors tend to focus additionally on the impact of COVID-19 on patients. The chapter consists of predictive and analytical models, inferences drawn from survey-based trials, and literature surveys. Proposed solutions for mental disorders using computational and survey-based methods are also included in the later sections of the chapter.