Fuzzy Cognitive Map scenario-based medical decision support systems for education

Area of Science:

• Artificial Intelligence
• Medical Informatics
• Computational Intelligence

Background:

• Soft Computing (SC) techniques leverage human knowledge for complex decision-making, crucial for Medical Decision Support Systems (MDSS).
• Fuzzy Cognitive Maps (FCMs) effectively model human reasoning for decision inference, leading to the development of FCM-MDSS.
• FCM-MDSS aid in critical decision-making, diagnosis support, and consulting medical professionals.

Purpose of the Study:

• To introduce a novel methodology for expanding the use of FCM-MDSS.
• To adapt FCM-MDSS for learning and educational purposes.
• To integrate a scenario-based learning (SBL) approach within FCM-MDSS.

Main Methods:

• Development of a new methodology integrating FCM-MDSS with SBL.
• Application of the methodology in a medical education context.
• Facilitation of "what-if" scenario exploration for trainees.

Main Results:

• The new methodology enhances the utility of FCM-MDSS for educational applications.
• SBL approach allows safe exploration of complex medical case studies.
• Future medical professionals can better prepare for adverse events.

Conclusions:

• FCM-MDSS, augmented with SBL, offers a valuable tool for medical education.
• This approach supports the development of critical thinking and decision-making skills in trainees.
• The methodology provides a safe environment for learning complex medical scenarios.