Abstract
Although today's advanced biomedical technology provides unsurpassed power in diagnosis, monitoring, and treatment, interpretation of vast streams of information generated by this technology often poses excessive demands on the cognitive skills of health-care personnel. In addition, storage, reduction, retrieval, processing, and presentation of information are significant challenges. These problems are most severe in critical care environments such as intensive care units (ICUs) and operating room (ORs) where many events are life-threatening and thus require immediate attention and the execution of definitive corrective actions. This article focuses on intelligent monitoring and control (IMC), or the use of artificial intelligence (AI) techniques to alleviate some of the common information management problems encountered in health-care environments. This article presents the findings of a survey of over 30 IMC projects. A major finding of the survey is that although significant advances have been made in introducing AI technology in critical care, successful examples of fielded systems are still few and far between. Widespread acceptance of these systems in critical care environments depends on a number of factors, including fruitful collaborations between clinicians and computer scientists, emphasis on evaluation studies, and easy access to clinical information.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
Abbreviations
- AI:
-
artificial intelligence
- ICU:
-
intensive care unit
- IMC:
-
intelligent monitoring and control
- OR:
-
operating room
References
Morris AH. Paradigms in management. In: Pinsky MR, Dhainaut J-FA, editors. Pathophysiologic Foundations of Critical Care. Baltimore, MD, 1993 193–206.
Wright D, Mackenzie SJ, Buchan I, Cairns CS, et al. Critical incidents in the intensive therapy unit. Lancet, September 1991; 338: 676–8.
Gardner RM, Hawley WL, East TD, Oniki TA, et al. Real time data acquisition: recommendations for the Medical Information Bus (MIB). International Journal of Clinical Monitoring and Computing 1992; 8: 251–8.
Fagan LM, Kunz JC, Feigenbaum EA, Osborn JJ. Extensions to the rule-based formalism for a monitoring task. In: Buchanan B, Shortliffe EH, editors. Rule-Based Expert Systems. Addison-Wesley Reading, MA, 1984: 397–423.
Sittig DF, Gardner RM, Morris AH, Wallace CJ. Clinical evaluation of computer-based respiratory care algorithms. International Journal of Clinical Monitoring and Computing 1990; 7 (3): 177–85.
Sittig DF, Pace NL, Gardner RM, Beck E, et al. Implementation of a computerized patient advice system using the HELP Clinical Information System. Computers and Biomedical Research 1989; 22: 474–87.
Henderson S, Crapo RO, Wallace J, East TD, et al. Performance of computerized protocols for the management of arterial oxygenation in an intensive care unit. International Journal of Clinical Monitoring and Computing 1992; 8: 271–80.
Henderson S, East TD, Morris AH, Gardner RM. Performance evaluation of computerized clinical protocols for management of arterial hypoxemia in ARDS patients. In: Proc. 13th Annual Symp. Comput. Appl. Med. Care. Washington, DC, 1989: 588–92.
Uckun S. Intelligent systems in patient monitoring and therapy management. Technical Report KSL-TR-93-32. Stanford University, 1993.
Hayes-Roth B, Washington R, Hewett R, Hewett M, et al. Intelligent monitoring and control. In: Proc. 11th International Joint Conf. on Artificial Intelligence. Detroit, MI, 1989: 243–9.
Clancey WJ. Heuristic classification. Artificial Intelligence 1985; 27: 289–350.
Haimowitz IJ, Kohane IS. Automated trend detection with multiple temporal hypotheses. In: Proc. 13th International Joint Conf. on Artificial Intelligence. Chambery, France, 1993.
Shahar Y, Musen MA. A temporal-abstraction mechanism for patient monitoring. In: Proc. 16th Annual Symp. Comput. Appl. Med. Care. Baltimore, MD, 1992.
Sittig DF, Factor M. Physiologic trend detection and artifact rejection: a parallel implementation of a multi-state Kalman filtering algorithm. Computer Methods and Programs in Biomedicine 1990; 31: 1–10.
Uckun S. An ontology for model-based reasoning in physiological domains. Ph.D. Dissertation, Vanderbilt University, Nashville, TN, 1992.
Cohn A, Rosenbaum S, Factor M, Miller PL. DYNASCENE: an approach to computer-basediintelligent cardiovascular monitoring using sequential clinial scenes. Methods of Information in Medicine 1990; 29: 122–31.
Steimann F, Adlassnig K-P. Clinical Monitoring with fuzzy automata. Technical Report MES-2/1993, University of Vienna, 1993.
Rule-Based Expert Systems. In: Buchanan B, Shortliffe EH, editors. Addison-Wesley Reading, MA, 1984.
Uckun S, Dawant BM. Qualitative modeling as a paradigm for diagnosis and prediction in critical care environments. Artificial Intelligence in Medicine 1992; 4 (2): 127–44.
Coiera EW. Monitoring diseases with empirical and model-generated histories. Artificial Intelligence in Medicine 1990; 2: 135–47.
Rutledge G. A method for the dynamic selection of models under time constraints. In: Proceedings of the AI and Statistics Conference. Ft. Lauderdale, FL, 1993.
Uckun S. Model-based reasoning in biomedicine. CRC Critical Reviews in Biomedical Engineering 1992; 19 (4): 261–92.
Farr BR, Shachter RD. Representation of preferences in decision support systems. In: Proc. 15th Annual Symp. Comput. Appl. Med. Care. Washington, DC, 1991: 1018–24.
Langlotz CP, Fagan LM, Tu SW, Sikic BI, et al. A therapy planning architecture that combines decision theory and artificial intelligence techniques. Computers and Biomedical Research 1987; 20: 279–303.
Leaning MS, Gallivan S, Newlands ES, Dent J, et al. Computer system for assisting with clinical interpretation of tumour marker data. British Medical Journal 1992; 305: 804–7.
Hayes-Roth B, Washington R, Ash D, Hewett R, et al. Guardian: a prototype intelligent agent for intensive-care monitoring. Artificial Intelligence in Medicine 1992; 4 (2): 165–85.
Dawant BM, Uckun S, Manders EJ, Lindstrom DP. Model-based signal acquisition, analysis, and interpretation for intelligent patient monitoring. IEEE EMBS Magazine, 1993.
Miller PL. Expert Critiquing systems: Practice-Based Medical Consultation by Computer. Springer-Verlag, New York, NY, 1986.
Doyle RJ, Fayyad UM. Sensor selection techniques in device monitoring. In: Proceedings of the 2nd Annual Conference on AI, Simulation, and Planning in High Autonomy Systems. Los Alamitos, CA, 1991: 154–63.
Dawant BM, Uckun S, Manders EJ, Lindstrom DP. SIMON: A distributed computer architecture for intelligent patient monitoring. Expert Systems with Applications, 1993.
van der Aa JJ. Intelligent alarms in anesthesia: a real time expert system application. Ph.D. Dissertation, Technische Universiteit Eindhoven, The Netherlands, 1990.
Westenskow DR, Orr JA, Simon FH, Bender H-J, et al. Intelligent alarms reduce anesthesiologist's response time to critical faults. Anesthesiology 1992; 77: 1074–9.
Garfinkel D, Matsiras PV, Lecky JH, Aukburg SJ, et al. PONI: an intelligent alarm system for respiratory and circulation management in the operating rooms. In: Proc. 12th Annual Symp. Comput, Appl. med. Care. Washington, DC, 1988: 13–17.
Kohane IS. Maintaining alternate interpretations of data from multiple sources in a clinical event monitoring system. In: Proceedings of the MEDINFO-92. Geneva, Switzerland, 1992: 483–9.
Musen MA. Dimensions of knowledge sharing and reuse. Computers and Biomedical Research 1992; 25: 435–67.
Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993; 5 (2): 93–106.
Dojat M, Brochard L, Lemaire F, Harf A. A knowledge-based system for assisted ventilation of patients in intensive-care units. International Journal of Clinical Monitoring and Computing 1992; 9: 239–50.
Strickland Jr JH, Hasson JH. A computer-controlled ventilator weaning system. Chest 1991; 100: 1096–9.
East T, Tolle CR, McJames S, Farrell RM, et al. A non-linear closed-loop controller for oxygenation based on a clinically proven fifth dimensional quality surface. Anesthesiology 1991; 75 (3A): A468.
Rutledge G, Thomson G, Farr B, Tovar M, et al. The design and implementation of a ventilator-management advisor. Artificial Intelligence in Medicine 1993; 5 (1): 67–82.
Uckun S, Dawant BM, Lindstrom DP. Model-based reasoning in intensive care monitoring: the YAQ approach. Artificial Intelligence in Medicine 1993; 5 (1): 31–48.
Tong DA. Weaning patients from mechanical ventilation: a knowledge-based system approach. In: Proc 14th Annual Symp. Comput. Appl. Med. Care. Washington, DC, 1990: 79–85.
Xu J, Hyman S, King P. Knowledge-based flash evoked potential recognition system. Artificial Intelligence in Medicine 1992; 4: 93–109.
Jiang A, King P, Smith B. Information interpretation in a real-time knowledge-based respiratory monitoring system. In: Ikeda et al., editor, Computing and Monitoring in Anesthesia and Intensive Care. Springer-Verlag Tokyo, 1992: 47–9.
Haimowitz IJ, Kohane IS. An epistemology for clinically significant trends. In: Proc. 11th National Conf. on Artificial Intelligence. Washington, DC, 1993.
Shahsavar N, Gill H, Wigertz O, Frostell C, et al. KAVE: a tool for knowledge acquisition to support artificial ventilation. Computer Methods and Programs in Biomedicine 1991; 34: 115–23.
Arkad K, Gill H, Ludwigs U, Shahsavar N, et al. Medical Logic Module (MLM) representation of knowledge in a ventilator treatment advisory system. International Journal of Clinical Monitoring and Computing 1991; 8: 43–8.
Beech M, Todd S, Tombs V. Knowledge-based techniques for alarm rationalisation in patient monitoring. In: Proceedings of the IEEE Colloquium on AI in Medical Decision Making, 1990.
Coiera EW. Qualitative superposition. Artificial Intelligence, 1992.
Miksch S, Horn W, Popow C, Paky F. VIE-VENT: knowledgebased monitoring and therapy planning of the artificial ventilation of newborn infants. In: Proceedings of the AIME-93. Munich, Germany, 1993.
Widman LE. A model-based approach to the diagnosis of the cardiac arrythmias. Artificial Intelligence in Medicine 1992; 4: 1–19.
Dawant BM, Uckun S, Lindstrom DP, Manders EJ. Modelbased signal analysis and interpretation in the intensive care unit. In: Proc. 14th Annual Conf. IEEE Engineering in Medicine and Biology Society. Paris, France, 1992: 874–5.
Factor M, Gelernter DH, Sittig DF. The multi-trellis software architecture and the intelligent cardiovascular monitor. Methods of Information in Medicine 1992; 31 (1): 44–55.
Factor M. The process trellis architecture for real-time monitors. In: Proc. 2nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Seattle, WA, 1990: 147–55.
Hayes S, Ciesielski VB, Kelly W. A comparison of an expert system and a neural network for respiratory system monitoring. Technical Report TR-92-01. Royal Melbourne Institute of Technology, 1992.
Hunter J, Chambrin M-C, Collinson P, Groth T, et al., INFORM: integrated support for decisions and activities in intensive care. International Journal of Clinical Monitoring and Computing 1991; 8: 189–99.
Rutledge G, Thomsen G, Farr B, Tovar M, et al. VentPlan: a ventilator management advisor. In: Proc. 15th Annual Symp. Comput. Appl. Med. Care. Washington, DC, 1991: 869–71.
Ash D, Gold G, Seiver A, Hayes-Roth B. Guaranteeing realtime response with limited resources. Artificial Intelligence in Medicine 1993; 5 (1): 49–66.
Alonso-Betanzos A, Moret-Bonillo V, Devoe LD, Searle JR. Obstetrical decision making based on predictive expert analysis. In: Proc. 13th Annual Conf. IEEE Engineering in Medicine and Biology Society. Orlando, FL, 1991: 1300–1.
Moret-Bonillo V, Alonso-Betanzos A, Truemper EJ, Garcia-Martin E, et al. PATRICIA: an expert system that incorporates a patient-oriented approach for the management of ICU patients. In: Proc. 14th Annual Conf. IEEE Engineering in Medicine and Biology Society. Paris, France, 1992: 876–7.
Alonso-Betanzos A. A connectionist approach to predict antenatal outcome. In: Proc. 14th Annual Conf. IEEE Engineering in Medicine and Biology Society. Paris, France, 1992: 1004-5.
Mora FA, Passariello G, Carrault G, Le Pichon J-P. Intelligent patient monitoring and management systems: a review. IEEE EMBS Magazine, 1993.
Larizza C, Moglia A, Stefanelli M M-HTP: a system for monitoring heart transplant patients. Artifical Intelligence in Medicine 1992; 4: 111–26.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Uckun, S. Intelligent system in patient monitoring and therapy management. J Clin Monit Comput 11, 241–253 (1994). https://doi.org/10.1007/BF01139876
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF01139876