Abstract
This paper presents work in progress on artificial intelligence in medicine (AIM) within the larger context of cognitive science. It introduces and develops the notion ofemergence both as an inevitable evolution of artificial intelligence towards machine learning programs and as the result of a synergistic co-operation between the physician and the computer. From this perspective, the emergence of knowledge takes placein fine in the expert's mind and is enhanced both by computerised strategies of induction and deduction, and by software abilities to dialogue, co-operate and function as a cognitive extension of the physician's intellectual capabilities. The proposed methodology gives the expert a prominent role which consists, first, of faithfully enunciating the descriptive features of his medical knowledge, thus giving the computer a precise description of his own perception of basic medicine, and secondly, of painstakingly gathering patients into computerised case bases which simulate exhaustive long-term memory. The AI capacities for knowledge elaboration are then triggered, giving rise to mathematically optimal diagnoses, prognoses, or treatment protocols which the physician may then evaluate, accept, reject, or adapt at his convenience, and finally append to a knowledge base. The idea of emergence embraces many issues concerning the purpose and intent of artificial intelligence in medical practice. Particularly, we address the representation problem as it is raised by classical decisional knowledge-based systems, and develop the notions of classifiers and hybrid systems as possible answers to this problem. Finally, since the whole methodology touches the problem of technological investment in health care, now inherent in modern medical practice, some ethical considerations accompany the exposé.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Amy, B. (1989). Contextual cognitive machines. In Tiberghien, G (ed.)Advancees in cognitive sciences. Vol 2: Theory and applications. Ellis Horwood. New York.
Amy, B. Giacometti, A., and Gut, A. (1990). Modèles connexionnistes de l'expertise. InProceed. NEURO NIMES '90. EC2. Nanterre, France. 99–119.
Andler, D. (ed.), (1992)Introduction aux sciences cognitives. Gallimard. Paris.
Barnett, G.O., Cimino, J.J., Hupp, J.A. and Hoffer, E.P. (1987). Dxplain: An evolving diagnostic decision support system. J Am.Med. Assoc.,3. 258.
Barsalou, L.W. and Hale, C.R., (1993) Component of conceptual representations: from feautres lists to recursive frames. In Van Mechelen, I. et al. (ed.)Categories and Concepts. Academic Press, New York.
Berner, E.S. Webster, G.D. Shugerman, A.A. Jackson, J.R. Algina, J., and Baker, A.L. (1994). Performance of four computer-based diagnostic systems.New England Journal of Medicine,330 (25). 1792–1796.
Beuscart, R., and Fieschi, M. (1992). Cognition et systèms experts medicaux.Le courrier du CNRS,79. 101.
Brooks, R.A. (1991). Intelligence without representation.Artificial intelligences,47. 139–159.
CCE (1992). EPIRIT:Specific Search and technological development in the field of information technology-Results and Progress 1991–1992. Commission of the European Communities. Luxembourg.
Changeux, J.-P., and Dahaene, S. (1989). Neuronal Models of Cognitive Functions.Cognition,33. 63–109.
Clancey, W.J. (1985). Heuristic Classification.Artificial Intelligence,27. 289–350.
Demongeot, J., Goles, E., and Tchuente, M. (ed.), (1985),Dynamical Systems and Cellular Automata. Academic Press, New York.
Demongeot, J., Hérve, T., Rialle, V. and Roche, C. (ed), (1988).Artificial Intelligence and Cognitive Sciences. Manchester University Press. New York.
Demongeot, J., Le Beuax, P., and Weil, G. (ed.), (1994).Informatisation de l'Unité de Soins du Futur. Springer-Verlag, Paris.
Dennett, D.C. (1991).Consciousness explained. Little-Brown-and-Co. Boston.
Feldman, J.A. (1989). Connectionist Representation of Concepts. In Pfeifer, R. et al. (ed.)Connectionism in perspective. North-Holland Publ. Amsterdam, The Netherlands. 24–45.
Forrest, D. (ed.), (1991)Emergent Computation. MIT Press, Cambridge, Massachusetts.
François, P. Robert, C., Cremilleux, B., Bucharles, C., and Demongoat, J. (1990). Variables processing in expert system building: Application to the aetiological diagnosis of infantile meningitis.Medical Informatics,15(2). 115–124.
Gallant, S.I. (1988) Connectionist expert systems.Communications of the ACM,2(31). 152–169.
Giacommeti, A., Iordanova, I., Amy, B., Vila, A., Reymond, F., Abaoub, L., Dahou, M., and Rialle, V. (1992). A Hybrid Approach to Computer Aided Diagnosis in Electromyography.14th Int Conf IEEE Engin Med Biol Soc,14. 1012–1013.
Grémy, F. (1988). Persons and Computers in Medicine and Health.Methods of Information in Medicine,27. 3–9.
Grémy, F. (1989). Human meaning of medical informatics: reflections on its future and trends.Medical Informatics,14(1). 1–11.
Hendler, J.A. (1989). On the need of hybrid systems.Connection Science (special issue on Hybrid Connectionist/Symbolic Systems),1(3).
Henery, R.J. King, R., Sutherland., Mitchell, J.M.O., and Brazdil, P. (1991). Statlog: Comparative Testing of Statistical and machine Learning Algorithms. InESPIRIT-Information Processing and Software: Results and Progress of Selected Projects. DG XIII. C.E.E. Bruxelles. 398–411.
Holland, J.H. (1986). Escaping brittleness: The Possibilities of General Purpose Learning Algorithmes Applied to Parallel Rule-Based Systems. In Michalski, R., Carbonel, J., and Mitchel, T. (ed.)Machine Learning. 2. Morgan-Kaufmann. Sen Mateo, CA. 594–623.
Hopfield, J.J. (1982). Neural Networks and physical Systems with Emergent Collective Computational Abilities.Proceedings of the National Academy of Science,79. 2554–2558.
Iordanova, I., Rialle, V., and Vila, A. (1992). Use of Unsupervised Neural Networks for Classification Tasks in Electromyographgy. Proc.14th Int Conf IEEE Engin Med Biol Soc,14. 1014–1015.
Kulikovski, C.A. and Weiss, S.M. (1982). Representation of expert knowledge for consultation: The Casnet and Expert projects. In Szolovits, P. (ed.)Artificial Intelligence in Medicine. Westview Press. Colarado.
Memmi, D. (1989). Connectionism and Artificial Intelligence. In Proceed.Neuro-Nimes '89. EC2. Nanterre, France. 17–34.
Meunier, J.G. (1992). Le Probléme de la catégorisation dans la representation de connaissances.Intellectica, (13–14). 353–356.
Meunier, J.G. (1993). Semiotic Primitives and conceptual representation of knowledge. In Jorna, R.J., Van Heusdenm, B., and Posner, R. (ed.)Sign, Search and Communication. Walter de Gruter. Berlin.
Miller, R.A., Masarie, F.E., Myers, J.D. (1986). Quick Medical Reference (QMR for diagnostic assistance.MD Computing,3 35–48.
MLT-Consortium (1993).MLT Project: Final Public Report. Commission of the European Community. Brussels.
Orsier, B., Iordanova, I., Rialle, V., Giacometti, A., and Vila, A. (1994). Hybrid systems for expertise modelling: from concepts to a medical application in electromyography.Computers and Artificial Intelligence,13(5). 423–440.
Patel, V.L. and Evans, D.A. (ed.), (1989).Cognitive Science in Medicine: Biomedical Modelling. MIT Press. Cambridge, Massachusets.
Patel, V.L. and Groen, G.J. (1987). Knowledge based solution strategies in medical reasoning,.Cognitive Science,10(1). 91–126.
Perry, C. (1990). Knowledge bases in Medicine: a review.Bull. Med. Libr. Assoc.,78(3). 271–282.
Pham, K.M., and Degoulet, P. (1991). MOSAIC: Medical Knowledge Processing Based on a Macro-Connectionist Approach to Neural Networks. InMEDINFO: Proc 6th Congress on Medical Informatics. Vol I. 82–86.
Pinkas, G. (1992). Requested Unrestricted First-Order Logic Formulas in Connectionist Networks. In Sun, R., and Bookman, L. A. (ed.) Proc. of the AAAI-92Workshop «Integrating Neural and Symbolic Processes-The Cognitive Dimension”. San Jose, California, 23–30.
Pollack, J.B. (1990) Recursive Distributed Representations.Artificial Intelligence 46. 77–105.
Posner, M. (ed), (1989).Foundation of Cognitive Science. MIT Press, Cambridge, MA.
Rialle, V. (1988). Data Analysis as an aid to Learning and Knowledge Base Making in a medical field. In Deomongoat, J. et al. (ed.)Artificial Intelligence and Cognitive Sciences. Manchester University Press. New York. 375–386.
Rialle, V. (1989). Pour une intégration des systèmes à bases de connaissance en practique clinique courante. InActes de Journées Francophones d'Informatique Médicale de Montpellier. Editions de l'Ecole Nationale de la Santé Publique, Rennes. 279–285.
Rialle, V. (1994).Décision et Cognition en Biomédicine: Modèles et Intégration. Mémoire de Diplôme d'Habilitation à Diriger des Recherces-informatique. Université Joseph Fourier, Grenoble.
Rialle, V. (1995). Vers la maîtrise informatique de la connaissance. In Joly, H. (ed.)Biomédicine 2000. Lavoiser, Paris. 52–75.
Rialle, V., Ohayon, M., Amy, B., Bessière, P. (1991a) Medical Knowledge Modeling in a Symbolic-Connectionist Perspective. In Nagel, J.H., and Smith, W.M. (ed.) 3th An. Int. Conf. IEEE Engin. in Med. and Biol. Society. 13(3) IEEE. Piscataway, NJ. 1109–1110.
Rialle, V., Pagnosis, D., Vermont, J., Augerat, P., and Giarardet, P. (1991b). Are expert systems able to assist intensive care?: Specific issues in the modeling of intensive care practice. In Pavé A., and Vansteenkiste, G.C. (ed.)Artificial intelligence in numerical and symbolic simulation Aléas, Lyon. 101–113.
Rialle, V., and Payette, D. (ed.), (1994).Modèles de la cognition: vers une science de l'espirit LEKTON, 4(2). Départment de Philosophie. Université du Québec à Montréal.
Rialle, V., and Stip, E. (1994). Modelisation cognitive en psychiatrie: des modèles symboliques aux modèles parallèles et distribués.Journal of Psychiatry and Neuroscience,19(3). 178–192.
Rialle, V., Stip, E., and O'Connor, K. (1994). Computer Mediated Psychotherapy: Ethical issues and difficulties in Implementation.Humane Medicine,10(3). 185–192.
Rialle, V., Vila, A., and Besnard, Y. (1991). Heterogeneous knowledge representation using a finite automaton and first order logic: A case study in Electromyography.Artificial Intelligence in Medicine,3(2). 65–74.
Riesbeck, C.K., and Schank, R.C. (1989).Inside Case-Based Reasoning. Lawrence Erlbaum. Hillsdale, New Jersey.
Rosch, E. (1978). Principles of categorization. In Rosch, E., and Lloyd, B.B. (ed.)Cognition and Categorization. Lawrence Erlbaum. Hillsdale, New jersey.
Rumelhart, D.E. McClelland, J.L., and PDP-Research-Group (ed.), (1986).Parallel Distributed Processing: Exploration in the Microstructure of Cognition. Vol 1: Foundations. MIT Press/Bradford Books. Cambridge, Massachusetts.
Shortliffe, E.H. (1976).Computer-Based Medical Consultation: MYCIN. American-Elsevier. New York.
Smolensky, P. (1986). Information Processing in Dynamical Systems: Foundation of Harmony Theory. In Rummelhart, D.E., McClelland, J.L., and PDP Reasearch-Group (ed.)Parallel Distributed Processing: Exploration in the Microstructure of Cognition. MIT Press. Cambridge, Massachusetts.
Summer, W. (1994). A review of Iliad and Quick Medical Reference for primary care providers. Two diagnostic computer programs.Arch. Fam. Med. 2(1). 87–95.
Sun, R., and Bookman, L.A. (ed.), (1992). Proc. of the AAAI-92 Workshop “Integrating Neural and Symbolic Processes-The Cognitive Dimension”. San Jose, California.
Thornton, C.J. (1992).Techniques in Computational Learning: An Introduction. Chapman & Hall. London.
Tiberghien, G. (ed.), (1989).Advances in cognitive science. Vol. 2. Theory and applications. Ellis Horwood. Chichester.
Touretzky, D.S. (1989). BolzCONS:Dynamic Symbol Structures in a Connectionist Network. Tech. Rep. No. CMU-CS-89-172, Carnegie Mellon University.
Varela, F., Thompson, E., and Rosch, E. (1991).The Embodied Mind: Cognitive Science and Human Experience. MIT Press, Cambridge, M.A.
Varela, F.J. and Bourgine, P. (ed.), (1992)Toward a Practice of Autonomous Systems. Proc. 1st Europ Conf Artificial Life. MIT Press. Cambridge, Massachusetts.
Weiss, S.M., and Kulikowski, C.A. (1991).Computer Systems that Learn: Classficiation and Prediction Methods from Statistics, Neural Nets, Machine Learning and Expert Systems, Morgan Kaufmann. San Mateo, California.
Weizenbaum, J. (1976).Computer power and human reason-From judgement to calculation. Freeman. San Francisco, CA.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rialle, V. Cognition and decision in biomedical artificial intelligence: From symbolic representation to emergence. AI & Soc 9, 138–160 (1995). https://doi.org/10.1007/BF01210601
Published:
Issue Date:
DOI: https://doi.org/10.1007/BF01210601