A Clustering Method to Identify Mental Health Patient Groups with Similar Treatment Outcomes

Abstract

A person's complete emotional, psychological, and social well-being is referred to as their mental health. It has an impact on how people feel, think, and act, as well as how they act and react to obstacles in life. Maintaining positive relationships, accomplishing goals, and living a satisfying life all depend on having good mental health. No matter what one's age, gender, race, or financial situation may be, mental health concerns can present themselves in a variety of ways and can affect everyone. Anxiety disorders, sadness, bipolar disorder, and schizophrenia are typical mental health issues. An individual's capacity to work, study, and sustain relationships can all be significantly impacted by mental health issues. Thankfully, there are a variety of treatments available, including counseling, medications, and dietary adjustments. Prioritizing mental health and getting treatment when needed are crucial. In the present study we analyze the treatments such as home treatments, early intervention and assertive outreach which were done focusing patients of United Kingdom. For this purpose, K-means clustering technique is used to cluster patients with similar disorders to categorize easily for their treatments. As a result of a considerable portion of the general population experiencing mental health issues at home point in their lives, mental health is a growingly important issue in the UK. Thus, this research will immensely help to get precautions at the correct time and to minimize mental disorders.