ARTIFICIAL INTELLIGENCE-BASED PERSONALIZED PREDICTIVE TREATMENT SYSTEM

Smart overview of the Invention

The invention introduces an AI-based system designed to provide personalized treatment plans for mental health disorders. By integrating EEG measurements with patient-specific data and AI algorithms, it offers tailored strategies that address each patient's unique needs. This approach enhances mental health care quality by creating a dynamic, patient-centered experience that improves outcomes and satisfaction while alleviating healthcare professionals' workload.

Background

Mental health disorders present a global challenge, requiring personalized treatments due to their complex nature. Traditional methods often rely on standardized plans, leading to suboptimal results. This system overcomes these limitations by using EEG insights and a wide array of patient factors to develop adaptive treatment plans. Options include various medications and therapies, ensuring a comprehensive approach that reflects the patient's life circumstances.

System Components

The system comprises several modules: a database of patient-specific factors, an EEG measurement module, and an AI-based treatment generation module. It analyzes data using AI algorithms, considering EEG signals and patient factors to create personalized plans. Treatment options span medication, psychotherapy, and other therapies. An evaluation module gathers feedback from patients and professionals, refining the treatment process.

Real-Time Monitoring

Real-time monitoring is achieved through wearable EEG devices, enabling continuous oversight of patients' conditions. The system detects significant changes in EEG patterns or symptoms, prompting timely interventions. It also tracks daily life factors like sleep and social interactions, allowing for accurate treatment adaptations that consider the interconnected nature of mental health.

Integration and Adaptation

The system integrates with existing electronic health records and remote monitoring platforms. It adapts treatment plans based on real-time data, ensuring they remain relevant and effective. By learning from previous outcomes, the AI refines its suggestions, offering diagnosis and prognosis insights while highlighting potential side effects. This innovation represents a significant advancement in personalized mental health care.