Modular Knowledge-Based Decision Support System Dedicated to a Cooperative Decision to Prevent Cardiovascular...

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Cardiovascular Disease Prevention

Background:

• Physicians exhibit reluctance towards adopting artificial intelligence (AI) decision support systems.
• Existing AI methods are often perceived as 'black boxes' (data-based) or rely on potentially contentious formalized knowledge (knowledge-based).
• There is a need for transparent and collaborative decision support tools in clinical practice.

Purpose of the Study:

• To introduce a novel modular decision support system for cardiovascular disease (CVD) prevention.
• To enhance cooperative decision-making between patients and physicians.
• To address physician hesitancy by employing a transparent, knowledge-based approach.

Main Methods:

• Development of a two-layer decision support system.
• Layer 1: A knowledge-based module for automated patient profiling and strategy generation.
• Layer 2: A dynamic, collaborative graphical user interface (GUI) for risk communication, motivation, and follow-up.

Main Results:

• The system generates patient profiles and associated prevention strategies.
• The collaborative GUI presents information on treatment adherence failure risks.
• Personalized motivation and follow-up strategies are provided to patients.

Conclusions:

• The presented system offers a transparent, knowledge-based approach to CVD prevention decision support.
• It facilitates a cooperative decision-making process between patients and physicians.
• Future work will focus on real-world assessment of the platform's efficacy.