Abstract
Situation awareness is known to be a critical skill in surgical decision making. While a few simulators have been developed to teach surgical decision making, none explicitly address teaching situation awareness skills. In this paper we present a knowledge representation framework that captures the key elements in reasoning about situation awareness. The framework makes use of concepts from AI planning and uses PDDL to represent surgical procedures. We describe tutorial feedback strategies identified in a preliminary observational study of endodontic surgery. We then present algorithms that implement these strategies using the knowledge representation framework. We show how the representation supports generating a number of tutorial interventions observed in teaching sessions by expert endodontic surgeons. We finally describe the contributions of our work.
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Acknowledgements
We thank the Faculty of Dentistry, Thammasat University for the support of the observational study. We gratefully acknowledge funding by the Hanse-Wissenschaftskolleg Institute for Advanced Study, Delmenhorst, Germany (Haddawy, Suebnukarn), the Santander BISIP Scholarship (Vannaprathip), and the Thailand Research Fund (RDG6050029).
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Vannaprathip, N., Haddawy, P., Schultheis, H., Suebnukarn, S. (2017). Generating Tutorial Interventions for Teaching Situation Awareness in Dental Surgery – Preliminary Report. In: Phon-Amnuaisuk, S., Ang, SP., Lee, SY. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2017. Lecture Notes in Computer Science(), vol 10607. Springer, Cham. https://doi.org/10.1007/978-3-319-69456-6_6
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