Monitoring-Based Model for Personalizing the Clinical Process of Crohn's Disease

Area of Science:

• Gastroenterology
• Biomedical Engineering
• Health Informatics

Background:

• Crohn's disease is a chronic inflammatory bowel disease requiring lifelong medical supervision.
• Individual patient characteristics necessitate personalized treatment and health recommendations.
• Current management approaches often lack cost-effective personalization.

Purpose of the Study:

• To propose a technology-based model for personalized Crohn's disease management.
• To develop a system architecture and prototype for functional validation.
• To leverage continuous monitoring and AI for tailored clinical processes.

Main Methods:

• Development of an information flow model (control, personalization, monitoring).
• Design of a service-based architecture and system prototype.
• Integration of diverse monitoring devices and AI algorithms for data analysis.

Main Results:

• A functional prototype integrating patient and environmental monitoring technologies was created.
• Artificial intelligence algorithms were incorporated to streamline data review and analysis.
• The system facilitates continuous and automated monitoring of Crohn's disease patients.

Conclusions:

• The proposed model enables personalized Crohn's disease management through continuous monitoring.
• AI-driven analysis reduces the burden of data interpretation.
• This approach supports the individualization of clinical processes for Crohn's patients.