Machine learning Application that using MBTI Classification to Understand Borderline Personality Disorder

This paper proposes the application of machine learning techniques using MBTI classification to gain a better understanding of Borderline Personality Disorder (BPD). BPD is a complex psychological disorder characterized by intense emotional instability, impulsive behaviors, and unstable relationships. By leveraging the strengths of machine learning algorithms and the insights provided by the Myers Briggs Type Indicator (MBTI), this approach aims to uncover patterns and identify distinct personality types associated with BPD. The MBTI classification system provides a framework for understanding individual differences in personality traits, preferences, and tendencies by categorizing individuals into one of 16 types. By analyzing the responses of individuals diagnosed with BPD to the MBTI questionnaire, machine learning algorithms can be trained to identify specific personality traits that are indicative of this disorder. The proposed approach has the potential to provide valuable insights into the underlying factors contributing to BPD and enhance diagnostic accuracy. In addition, it may facilitate the development of personalized treatment plans and interventions that target the specific needs and challenges of individuals with BPD.