Use of AI and Mathematical Modelling in Mental Health: Exploring Paroxysmal Supraventricular Tachycardia, Personality Disorders, and Body Image Perception

Use of AI and Mathematical Modelling in Mental Health: Exploring Paroxysmal Supraventricular Tachycardia, Personality Disorders, and Body Image Perception This thesis applies AI and mathematical modelling to uncover psychological patterns in Paroxysmal Supraventricular Tachycardia (PSVT) and to study the evolution of mental health in relation to distorted Body Image Perception. To achieve these objectives, two separate studies were conducted, collecting data from 172 and 330 participants, respectively. In both cases, participants completed psychological questionnaires tailored to the specific aims of each study. Regarding the PSVT study, statistical and factor analyses were performed to identify key psychological patterns, while several machine learning models were tested to distinguish affected patients from controls. In addition, feature selection techniques helped investigate the key psychological scales. Focusing on the second study, a recursive mathematical model was developed to describe the evolution of a unidimensional psychological variable (PSYCH), which captures concerns about body shape, weight, self-esteem, and depressive tendencies. Implemented in Matlab-Simulink, the model was analyzed through time-domain simulations, examining stability and long-term behavior. Through AI and mathematical modelling, this research identifies psychological patterns in PSVT and presents a new method for exploring body image dynamics within an engineering framework. The findings contribute to a deeper understanding of psychological and sociocultural factors, providing a foundation for further research and clinical applications.