A constrained disorder principle-based second-generation artificial intelligence digital medical cannabis system: A real-world data analysis

Abstract Introduction: Adhering to treatment plans can be challenging for medical cannabis patients. According to the constrained-disorder principle (CDP), biological systems are defined by their degree of variability. CDP-based second-generation artificial intelligence (AI) systems use personalized variability signatures to improve chronic medication response. Aim: We retrospectively analyzed real-world data regarding chronic pain patients using the second generation of artificial intelligence systems to improve adherence to medical cannabis and increase its effectiveness. Design and methods: A retrospective analysis of real-world data