Abstract
Explicit representation of time and change is an essential feature for building systems that are supposed to interact with real-world dynamic environments. In this paper, we propose to use the Cached Event Calculus (CEC), an improved version of the Event Calculus [Ko86], to represent temporal aspects in intelligent medical monitoring systems. In particular, we explore the application of CEC to the management of mechanical ventilation, using it to interpret change in data over time, assess patient status and its evolution, and choose the proper level of mechanical assistance.
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References
Brochard L., Pluskwa F., Lemaire F. Improved efficacy of spontaneous breathing with inspiratory pressure support, American Review of Respiratory Disease, vol.136, 411–415, 1987.
Chittaro L., Montanari A., Provetti A. Skeptical and Credulous Event Calculi for Supporting Modal Queries, Proc. ECAI '94: 11th European Conference on Artificial Intelligence, Amsterdam, The Netherlands, John Wiley and Sons, 361–365, 1994.
Chittaro L., Montanari A. Efficient Temporal Reasoning in the Cached Event Calculus, to appear in Computational Intelligence Journal, 1996.
Cohn A.I., Rosenbaum S., Factor M. and Miller P.L., DYNASCENE: An approach to computer-based intelligent cardiovascular monitoring using sequential clinical “scenes”, Methods of Information in Medicine, vol. 29, 122–131, 1990.
Dechter R., Meiri I. and Judea P. Temporal constraints networks, Artificial Intelligence, vol. 4, 61–95, 1991.
Dojat M., Brochard L., Lemaire F. and Harf A. A knowledge-based system for assisted ventilation of patients in intensive care, International Journal of Clinical Monitoring and Computing, vol. 9, 239–250, 1992.
Dojat M. and Sayettat C. A realistic model for temporal reasoning in real-time patient monitoring, to appear in Applied Artificial Intelligence Journal, 1995.
Fagan L.M. Representing time dependant relations in a medical setting, Ph.D. thesis, Stanford University, 1980.
Hayes-Roth B., et al. Guardian: a prototype intelligent agent for intensive-care monitoring, Artificial Intelligence in Medicine, vol. 4, 165–185, 1992.
Kowalski R.A. and Sergot M.J. A logic-based calculus of events, New generation computing, vol. 4, 67–95, 1986.
Lau F., and Vincent D. D. Formalized decision support for cardiovascular intensive care, Computers and Biomedical Research, vol. 26, 294–309, 1993.
MacIntyre N.R. Respiratory function during pressure support ventilation, Chest, vol. 89, 677–683, 1986.
Rasmussen J., Diagnostic reasoning in action, IEEE Transactions on Systems, Man and Cybernetics, vol. 23, 981–992, 1993.
Rutledge G.W. Thomsen G.E., Farr B.R., Tovar M.A., et al., The design and implementation of a ventilator-management advisor, Artificial Intelligence in Medicine, vol. 5, 67–82, 1993.
Sittig D.F. A computerized patient advice system to direct ventilatory care, Ph.D. thesis, University of Utah, 1988.
Shoham Y. Temporal logic in AI: semantical and onthological considerations, Artificial Intelligence, vol. 33, 89–104, 1987.
Shortliffe, E.H. Clinical decision support systems in medical informatics, in Computer applications in health care, eds. E. H. Shortliffe and A. Perrault, Reading: Addison Wesley, 466–501, 1990.
Stefanelli M., Lanzola G., and Ramoni M. Knowledge acquisition based on an epistemological model of medical reasoning, Proc. IEEE-EMBS, vol 3, Paris, 880–882, 1992.
Tong, D.A. Weaning patients from mechanical ventilation. A knowledge-based approach. Computer methods and programs in biomedicine, 35, 2677–278, 1991.
Uckun S. Intelligent systems in patient monitoring and therapy management, Technical Report KSL 93-32, Stanford University, 1993.
Van Beek P. Reasoning about qualitative temporal information, Artificial Intelligence, vol. 58, 297–326, 1992.
Van de Graaff W.B., et al. Pressure support. Changes in ventilatory pattern and components of the work of breathing, Chest, vol. 100, 1082–89, 1991.
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© 1995 Springer-Verlag Berlin Heidelberg
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Chittaro, L., Del Rosso, M., Dojat, M. (1995). Modeling medical reasoning with the Event Calculus: an application to the management of mechanical ventilation. In: Barahona, P., Stefanelli, M., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIME 1995. Lecture Notes in Computer Science, vol 934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60025-6_127
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DOI: https://doi.org/10.1007/3-540-60025-6_127
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