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Logic engineering in medicine

Published online by Cambridge University Press:  07 July 2009

Peter J. F. Lucas
Affiliation:
Department of Computer Science, Utrecht University, Padualaan 14, 3584 CH Utrecht, The Netherlands (e-mail: [email protected])

Abstract

The safety-critical nature of the application of knowledge-based systems to the field of medicine requires the adoption of reliable engineering principles with a solid foundation for their construction. Logical languages with their inherent, precise notions of consistency, soundness and completeness provide such a foundation, thus promoting scrupulous engineering of medical knowledge. Moreover, logic techniques provide a powerful means for getting insight into the structure and meaning of medical knowledge used in medical problem solving. Unfortunately, logic is currently only used on a small scale for building practical medical knowledge-based systems. In this paper, the various approaches proposed in the literature are reviewed, and related to the various types of knowledge and problem solving employed in the medical field. The appropriateness of logic for building medical knowledge-based expert systems is further motivated.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1995

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References

Adlassnig, K-P, Kolarz, G, Scheithauser, G, Effenberger, W and Grabner, G, 1985. “CADIAG: approaches to computer-assisted medical diagnosisComp. Biol. Med. 15 315335.CrossRefGoogle Scholar
Aït-Kaci, H and Podelski, A, 1993. “Towards a meaning of lifeJ. Logic Programming 16 195234.Google Scholar
Aït-Kaci, H and Nasser, R, 1986. “LOGIN: A logic programming language with built-in inheritanceJ. Logic Programming 3 185215.CrossRefGoogle Scholar
Besnard, P. 1989. An Introduction to Default Logic. Springer-Verlag.CrossRefGoogle Scholar
Bezem, M. 1986. “Consistency of rule-based expert systems” In: Lusk, E and Overbeek, R (eds) Proceedings 9th International Conference on Automated Deduction 151161, Springer-Verlag.Google Scholar
Bratko, I, Mozetiĉ, I and Lavraĉ, N, 1989. KARDIO: A Study in Deep and Qualitative Knowledge for Expert Systems. MIT Press.Google Scholar
Buchanan, BG, and Shortliffe, EH, 1984. Rule-based Expert Systems: the MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley.Google Scholar
Bylander, T, Allemang, D, Tanner, MC and Josephson, JR, 1992. “The computational complexity of abduction” In: Brachman, RJ, Levesque, HJ and Reiter, R (eds) Knowledge Representation 2560, MIT Press.Google Scholar
Chang, CL and Lee, RCT, 1973. Symbolic Logic and Mechanical Theorem Proving. Academic Press.Google Scholar
Charniak, E and McDermott, D, 1985. Introduction to Artificial Intelligence. Addison-Wesley.Google Scholar
Clancey, WJ, 1985. “Heuristic classificationArtificial Intelligence 27 289350.CrossRefGoogle Scholar
Clark, DA, Fox, J, Glowinski, AJ and O'Neil, MJ, 1990. “Symbolic reasoning for decision making” In: Borcherding, K, OI, Larichev and Messick, DM (eds) Contemporary Issues in Decision Making 5775, Elsevier.Google Scholar
Cohen, PR, 1985. Heuristic Reasoning about Uncertainty: An Artificial Intelligence Approach. Pitman.Google Scholar
Coiera, EW, 1990. “Monitoring diseases with empirical and model-generated historiesArtificial Intelligence in Medicine 2 135147.CrossRefGoogle Scholar
Coiera, EW, 1992. “The qualitative representation of physical systemsThe Knowledge Engineering Review 17(1) 5577.CrossRefGoogle Scholar
Console, L, Dupré, DT and Torasso, P, 1989. “A theory of diagnosis for incomplete causal models” In: Proceedings 10th International Joint Conference on Artificial Intelligence 13111317.Google Scholar
Console, L and Torasso, P, 1990a. “Hypothetical reasoning in causal modelsInternational Journal of Intelligent Systems 5 83124.CrossRefGoogle Scholar
Console, L and Torasso, P, 1990b. “Integrating models of correct behaviour into abductive diagnosis” In: Proceedings of ECAI'90 160166.Google Scholar
Console, L and Torasso, P, 1991a. “A spectrum of logical definitions of model-based diagnosisComputational Intelligence 7(3) 133141.CrossRefGoogle Scholar
Console, L and Torasso, P, 1991b. “On the co-operation between abductive and temporal reasoning in medical diagnosisArtificial Intelligence in Medicine 3(3) 291311.CrossRefGoogle Scholar
Das, SK, Clarke, M and Fox, J, 1993. “A logic for reasoning about safety in decision support systems” In: 2nd European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty Granada.Google Scholar
VanDenneheuvel, S Denneheuvel, S, VanEmde Boas, P Emde Boas, P, DeGeus, F Geus, F and Rotterdam, E, 1990. “RL, a language for constraint solving” In: Logic Programming and Database Processing Computer Science in the Netherlands.Google Scholar
Dicbas, M, VanHentenryck, P Hentenryck, P, Simonis, H, Aggoun, A, Graft, T and Berthier, F, 1988. “The constraint logic programming language CHIP” In: Proceedings of the International Conference in Fifth Generation Computer Systems Tokyo, Japan.Google Scholar
De Dombal, FT, Dallos, V and McAdam, WA, 1991. “Can computer-aided teaching packages improve clinical care in patients with acute abdominal pain?British Medical Journal 302 14951497.CrossRefGoogle ScholarPubMed
Duda, RO, Hart, PE and Nilsson, NJ, 1976. “Subjective Bayesian methods for rule-based inference systems” In: AFIPS Conference Proceedings of the 1976 National Computer Conference 45 10751082.Google Scholar
Ehrig, H and Mahr, B, 1985. Fundamentals of Algebraic Specification I: Equations and Initial Semantics Monographs on Theoretical Computer Science 6, Springer-Verlag.CrossRefGoogle Scholar
Ehrig, H and Mahr, B, 1990. Fundamentals of Algebraic Specification II: Module Specifications and Constraints Monographs on Theoretical Computer Science 21, Springer-Verlag.Google Scholar
First, MB, Weimer, BJ, McLinden, S and Miller, RA, 1982. “LOCALIZE: computer-assisted localization of peripheral nervous system lesionsComputers and Biomedical Research 15 525543.CrossRefGoogle ScholarPubMed
Fox, J, 1993. “On the soundness and safety of expert systemsArtificial Intelligence in Medicine 5 159179.Google Scholar
Fox, J, Clark, DA, Glowinski, A and O'Neil, MJ, 1990. “Using predicate logic to integrate qualitative reasoning and classical decision theoryIEEE Transactions on Systems, man, and Cybernetics 20 347357.Google Scholar
Fox, J, Gordon, C, Glowinski, AJ and O'Neil, M, 1990. “Logic engineering for knowledge engineering: the Oxford System of MedicineArtificial Intelligence in Medicine 2 323339.CrossRefGoogle Scholar
Futatsugi, K, Goguen, JA, Jouannaud, JP and Meseguer, J, 1985. “Principles of OBJ2” In: Proceedings of the Symposium on Principles of Programming Languages 5266, ACM.CrossRefGoogle Scholar
Genesereth, MR and Nilsson, NJ, 1987. Logical Foundations of Artificial Intelligence. Morgan Kaufmann.Google Scholar
De Geus, F, Rotterdam, E, Van Denneheuvel, S and Van Emde Boas, P, 1991. “Physiological modelling using RL” In: Stefanelli, M, Hasman, A, Fieschi, M and Talmon, J (eds) AIME91: Lecture Notes in Medical Informatics 198210, Springer-Verlag.Google Scholar
Grodins, FS, 1963. Control Theory and Biological Systems. Columbia University Press.Google Scholar
Hammond, P, Davenpor, JC and Fitzpatrick, FJ, 1993. “Logic-based integrity constraints and the design of dental prosthesesArtificial Intelligence in Medicine 5(5) 431446.Google Scholar
Hammond, P, Harris, AL, Das, KS and Wyatt, JC, 1994. “Safety and decision support in oncologyMeth. Inf Med. 33(4) 371381.Google Scholar
Hammond, P, and Davenport, JC, 1995. “Eliciting and modelling the design knowledge of multiple experts” submitted for publication.Google Scholar
Hammond, P and Sergot, M, 1995. “Computer support for protocol-based treatment of cancer” J. Logic Programming, to appear.CrossRefGoogle Scholar
Van Harmelen, F, 1991. Meta-level Inference Systems. Pitman.Google Scholar
Van Harmelen, F and Balder, J, 1992. “(ML)2: a formal language for KADS models of expertiseKnowledge Acquisition 4 127161.Google Scholar
Hill, PM and Lloyd, JW, 1994. The Gödel Programming Language. MIT Press.Google Scholar
Hayes, PJ, 1979. “The logic of frames” In: Metzing, D (ed) Frame Conception and Text Understanding 46–61, Walter de Gruyter and Co., Berlin.Google Scholar
Van Hentenryck, P, 1991. “Constraint logic programmingThe Knowledge Engineering Review 6(3) 151194.CrossRefGoogle Scholar
Hickam, DH, Shortliffe, EH and Bishoff, MB, 1985. “The treatment advice of a computer-based cancer chemotherapy protocol advisorAnnals of Internal Medicine 103 928936.Google Scholar
Hrycej, T, 1993. “A temporal extension of PrologJ. Logic Programming 16 114145.Google Scholar
Huang, J, Fox, J, Gordon, C and Jackson-Smale, A, 1993. “Symbolic decision support in medical careArtificial Intelligence in Medicine 5(5) 415430.CrossRefGoogle ScholarPubMed
Jaffar, J and Lassez, J-L, 1987. “Constraint Logic Programming” In: Proceedings of the 14th POPL 111119.CrossRefGoogle Scholar
Jaffar, J and Maher, MJ, 1994. “Constraint logic programming: a surveyJ.Logic Programming 19 503581.Google Scholar
Jaspers, RBM, 1990. Medical Decision Support: an Approach in the Domain of Brachial Plexus Injuries PhD thesis, Delft University of Technology.Google Scholar
Josephson, JR and Josephson, SG, 1994. Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press.Google Scholar
O'Keefe, RM, Balci, O and Smith, EP, 1987. “Validating expert system performanceIEEE Expert 4 8189.CrossRefGoogle Scholar
Kim, JH and Pearl, J, 1983. “A computational model for causal and diagnostic reasoning in inference systems” In: Proceedings 8th International Joint Conference on Artificial Intelligence 190–193, Karlsruhe.Google Scholar
De Kleer, J, Mackworth, AK and Reiter, R, 1992. “Characterizing diagnosis and systemsArtificial Intelligence 56 197222.Google Scholar
Konolige, K, 1992. “Using default and causal reasoning in diagnosis” In: Proceedings Workshop on Principles of Knowledge Representation and Reasoning Boston.Google Scholar
Kowalski, RA, 1979. Logic for Problem Solving. North-Holland.Google Scholar
Kowalski, RA and Sergot, MJ, 1986. “A logic-based calculus of eventsNew Generation Computing 4(1) 6795.Google Scholar
Kowaiski, RA, 1990. “Problems and promises of computational logic” In: Lloyd, JW (ed) Computational Logic, 135, Springer-Verlag.Google Scholar
Krause, P and Glowinski, A, 1993. “Formal specification and medical decision supportApplied Artificial Intelligence 7 237256.CrossRefGoogle Scholar
Krause, P, Ambler, S, Elvang-Coransson, M and Fox, J, 1995. “A logic of argumentation for reasoning under uncertaintyComputational Intelligence 11, to appear.Google Scholar
Kuipers, BJ, 1986. “Qualitative simulationArtificial Intelligence 29 289388.CrossRefGoogle Scholar
Kuipers, BJ, 1994. Qualitative Reasoning. MIT Press.Google Scholar
Kulikowski, CA and Weiss, SM, 1982. “Representation of expert knowledge for consultation: the CASNET and EXPERT projects” In: Szolovits, P (ed) Artificial Intelligence in Medicine 21–55, Westview Press, Boulder, Co.Google Scholar
Lloyd, JW, 1987. Foundations of Logic Programming, 2nd ed. Springer-Verlag.Google Scholar
Łukaszewicz, W, 1990. Non-monotonic Reasoning: Formalization of Commonsense Reasoning. Ellis Horwood.Google Scholar
Lucas, PJF and Van der Gaag, LC, 1991. Principles of Expert Systems. Addison-Wesley.Google Scholar
Lucas, PJF and Janssens, AR, 1991. “Development and validation of HEPAR, an expert system for the diagnosis of disorders of the liver and biliary tractMedical Informatics 16 259270.Google Scholar
Lucas, PJF, 1993. “The representation of medical reasoning models in resolution-based theorem proversArtificial Intelligence in Medicine 5(5) 395414.CrossRefGoogle ScholarPubMed
Maes, P and Nardi, D, 1988. Meta-level Architectures and Reflection. North-Holland.Google Scholar
Macartney, FJ, 1988. “Diagnostic logic” In: Philips, C (ed) Logic in Medicine British Medical Journal, London.Google Scholar
McCabe, FG, 1992. Logic and Objects. Prentice-Hall.Google Scholar
Miller, AM, Pople, HE and Myers, JD, 1982. “INTERNIST-I, an experimental computer-based diagnostic consultant for general internal medicineNew England Journal of Medicine 307 468476.CrossRefGoogle ScholarPubMed
McCune, WW, 1990. OTTER 2.0 Users' Guide. Report ANN-88/44, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois.Google Scholar
Morik, K, Potamias, G, Moustakis, V and Charissis, G, 1993. “Model-based learning support to knowledge acquisition: a clinical case study” In: Andreassen, S (ed) Artificial Intelligence in Medicine 434439, IOS Press.Google Scholar
Moser, W and Adlassnig, K-P, 1992. “Consistency checking of binary categorical relationships in a medical knowledge baseArtificial Intelligence in Medicine 4 389407.Google Scholar
Muggleton, S, 1992. “Inductive logic programming” In: Muggleton, S (ed) Inductive Logic Programming 327, Academic Press.Google Scholar
Patil, RS, Szolovits, P and Schwartz, WB, 1992. “Modelling knowledge of the patient in acid-base and electrolyte disorders” In: Szolovits, P (ed) Artificial Intelligence in Medicine 191226, Westview Press, Boulder Co.Google Scholar
Pearl, J, 1988. Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann.Google Scholar
Peng, Y and Reggia, JA, 1990. Abductive Inference Models for Diagnostic Problem Solving. Springer-Verlag.CrossRefGoogle Scholar
Pople, HE, 1973. “On the mechanization of abductive logic” In: Proceedings 3rd International Joint Conference on Artificial Intelligence.Google Scholar
Pople, HE, 1977. “The formation of composite hypotheses in diagnostic problem solving: an exercise in synthetic reasoning” In: Proceedings 5th International Joint Conference on Artificial Intelligence.Google Scholar
Pople, HE, 1982. “Heuristic methods for imposing structure on ill-structured problems: the structuring of medical diagnosis” In: Szolovits, P (ed) Artificial Intelligence in Medicine 119190, Westview Press, Boulder Co.Google Scholar
Reggia, J, 1978. “A production system for neurological localization” In: Proceedings 2nd Annual Symposium on Computer Applications in Medical Care 254260.Google Scholar
Reiter, R, 1978. “On closed world databases” In: Gallaire, H and Minker, J (eds) Logic and Databases. Springer-Verlag.Google Scholar
Reiter, R, 1987. “A theory of diagnosis from first principleArtificial Intelligence 32 5795.CrossRefGoogle Scholar
Shachter, RD, 1986. “Evaluating influence diagramsOperation Research 34(6) 871882.Google Scholar
Shortliffe, EH, 1991. “Knowledge-based systems in medicine” In: Adlassnig, K-P, Grabner, G, Bengtsson, S and Hansen, R (eds) Medical Informatics Europe 1991 59, Springer-Verlag.Google Scholar
Shortliffe, EH and Buchanan, BG, 1975. “A model of inexact reasoning in medicineMathematical Biosciences 23 351379.Google Scholar
Smets, P, Mamdani, A, Dubois, D and Prade, H (eds) 1988. Non-Standard Logics for Automated Reasoning. Academic Press.Google Scholar
Sommer, A, Emde, W, Kietz, J-U and Wrobel, S, 1994. MOBAL 3.0 User Guide, German National Research Centre for Computer Science (GMD), Al Research Division 13.KI, St. Augustin.Google Scholar
Soper, P, Ranaboldo, C and Abeysinghe, G, 1991. “A temporal model for clinical and resource management in vascular surgery” In: Karagiannis, D (ed) Database and Expert Systems Applications. 549552, Springer-Verlag.Google Scholar
Spivey, JM, 1989. The Z Notation: A Reference Manual. Prentice Hall.Google Scholar
Sterling, L and Shapiro, E, 1986. The Art of Prolog. MIT Press.Google Scholar
Stickel, M, 1986. “An introduction to automated deduction” In: Bibel, W and Jorrand, Ph (eds) Fundamentals of Artificial Intelligence 75132, Springer-Verlag.CrossRefGoogle Scholar
Stickel, M, 1988. “A Prolog technology theorem prover: implementation by an extended Prolog compilerJ. Automated Reasoning 4(4) 353380.CrossRefGoogle Scholar
Todd, BS, 1994. “A probablistic simulation model to assist the localization of nerve lesionsMedical Informatics 19(3) 209227.Google Scholar
Torasso, P and Console, L, 1989. Diagnostic Problem Solving: Combining Heuristic, Approximate and Causal Reasoning. North Oxford Academic Publishers.Google Scholar
Touretzky, DS, 1986. The Mathematics of Inheritance Systems. Pitman.Google Scholar
Tuhrim, S, Reggia, J and Goodall, S, 1991. “An experimental study of criteria for hypothesis plausibilityJ. Experimental and Theoretical Artificial Intelligence 3 129144.CrossRefGoogle Scholar
Turner, R, 1984. Logics for Artificial Intelligence. Ellis Horwood.Google Scholar
Weyhrauch, RW, 1980. “Prolegomena to a theory of mechanized formal reasoningArtificial Intelligence 13 133170.Google Scholar
Wos, L, Overbeek, R, Lusk, E and Boyle, J, 1992. Automated Reasoning: Introduction andApplications, 2nd ed. Prentice-Hall.Google Scholar
Wos, L, 1988. Automated Reasoning: 33 Basic Research Problems. Prentice-Hall.Google Scholar
Wrobel, S, 1990. Application of MOBAL to the Medical Domains of ICS/FORTH. Technical Note, GMD, P2154/31/l/Google Scholar
TD, Wu, 1991. “A problem decomposition method for efficient diagnosis and interpretation of multiple disordersComputer Methods and Programs in Biomedicine 35 239250.Google Scholar
Wyatt, J and Spiegelhalter, DJ, 1990. “Evaluating medical expert systems: what to test for and how?Medical Informatics 15(3) 205217Google Scholar