Synaptic Harmonies: Applying Graph Coloring Algorithms to Mental Health AI Systems

Abstract

Current healthcare systems need advanced technology answers to treat effectively the mental disorders patients’ experience. Artificial Intelligence shows us multiple ways to improve mental health treatment customized specifically for everyone. Graph coloring principles help us design better mental health AI technologies. Our graph theory techniques help improve how AI mental health solutions match patients to therapists while distributing resources effectively. Graph coloring lets us structure how patients, therapists, and resources work together so our scheduling and resource use stay conflict-free and efficient. Our approach lets healthcare providers design unique treatment sessions that cater to different patient requirements. Our research shows how combining medical treatment systems and computer algorithms can organize better mental healthcare delivery. By combining mathematical systems and mental health AI tools we create a better way to handle both large numbers of patients and improve their treatment quality.