Conference Paper

A Machine Learning Approach to the Detection of Fetal Hypoxia during Labor and Delivery.

Conference: Proceedings of the Twenty-Second Conference on Innovative Applications of Artificial Intelligence, July 11-15, 2010, Atlanta, Georgia, USA
Source: DBLP
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Available from: Robert Edward Kearney, Jan 27, 2014
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    ABSTRACT: Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.