Effective domain-dependent reuse in medical knowledge bases.

Knowledge reuse is now a critical issue for most developers of medical knowledge-based systems. As a rule, reuse is addressed from an ambitious, knowledge-engineering perspective that focuses on reusable general purpose knowledge modules, concepts, and methods. However, such a general goal fails to take into account the specific aspects of medical practice. From the point of view of the knowledge engineer, whose goal is to capture the specific features and intricacies of a given domain, this approach addresses the wrong level of generality. In this paper, we adopt a more pragmatic viewpoint, introducing the less ambitious goal of "domain-dependent limited reuse" and suggesting effective means of achieving it in practice. In a knowledge representation framework combining objects and production rules, we propose three mechanisms emerging from the combination of object-oriented programming and rule-based programming. We show these mechanisms contribute to achieve limited reuse and to introduce useful limited variations in medical expertise.

[1]  M. Pinsky,et al.  The Pathophysiologic Foundations of Critical Care , 2019, Critical Care Nephrology.

[2]  Jean-Pierre Briot,et al.  Actalk: A Testbed for Classifying and Designing Actor Languages in the Smalltalk-80 Environment , 1989, ECOOP.

[3]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[4]  Tony Owen.  Readings in Medical Artificial Intelligence: The First Decade, edited by William J. Clancey and Edward H. Shortcliffe Addison-Wesley Publishing Company, Massachusetts, USA, 1984 (£41.95) , 1988, Robotica.

[5]  S Uckun,et al.  Intelligent systems in patient monitoring and therapy management. A survey of research projects. , 1994, International journal of clinical monitoring and computing.

[6]  Lawrence M. Fagan.  VM, representing time-dependent relations in a medical setting , 1980 .

[7]  Bernhard Nebel,et al.  Reasoning and Revision in Hybrid Representation Systems , 1990, Lecture Notes in Computer Science.

[8]  Reed M. Gardner,et al.  Patient-monitoring systems , 1990 .

[9]  Paul R. Cohen,et al.  A declarative representation of control knowledge , 1989, IEEE Trans. Syst. Man Cybern..

[10]  K Fitzpatrick,et al.  Computer applications in health care. , 1993, Physician assistant.

[11]  M Dojat,et al.  Evaluation of a knowledge-based system providing ventilatory management and decision for extubation. , 1996, American journal of respiratory and critical care medicine.

[12]  Ronald J. Brachman,et al.  An overview of the KL-ONE Knowledge Representation System , 1985 .

[13]  François Pachet,et al.  On the Embeddability of Production Rules in Object-Oriented Languages , 1995, J. Object Oriented Program..

[14]  Jeanette X. Polaschek,et al.  The design and implementation of a ventilator-management advisor , 1993, Artif. Intell. Medicine.

[15]  François Pachet,et al.  Rule firing with metarules , 1994, SEKE.

[16]  Mario Tokoro,et al.  Experience and evolution of concurrent Smalltalk , 1987, OOPSLA 1987.

[17]  Lee D. Erman,et al.  Distributed intelligent control and management: concepts, methods and tools for developing DICAM applications , 1992, Proceedings Fourth International Conference on Software Engineering and Knowledge Engineering.

[18]  M. Ramoni,et al.  An epistemological framework for medical knowledge-based systems , 1992, IEEE Trans. Syst. Man Cybern..

[19]  Patrick Henry Winston,et al.  The psychology of computer vision , 1976, Pattern Recognit..

[20]  Bernhard Nebel,et al.  An Empirical Analysis of Terminological Representation Systems , 1992, Artif. Intell..

[21]  Edward H. Shortliffe,et al.  The adolescence of AI in medicine: will the field come of age in the '90s? , 1993, Artif. Intell. Medicine.

[22]  Phillip M. Yelland.  Experimental Classification Facilities for Smalltalk , 1992, OOPSLA.

[23]  Silvana Quaglini,et al.  Hybrid knowledge-based systems for therapy planning , 1992, Artif. Intell. Medicine.

[24]  F. BARACHINI,et al.  Production systems for process control: Advances and experiences , 1993, Appl. Artif. Intell..

[25]  Thomas R. Gruber.  Acquiring Strategic Knowledge from Experts , 1988, Int. J. Man Mach. Stud..

[26]  Allen Newell,et al.  The Knowledge Level , 1989, Artif. Intell..

[27]  Barbara Hayes-Roth,et al.  A Blackboard Architecture for Control , 1985, Artif. Intell..

[28]  Gary S. Kahn,et al.  The Mud System , 1986, IEEE Expert.

[29]  A. Casey,et al.  PACE project: object-orientated modelling of paediatric practice. , 1992, Medical informatics = Medecine et informatique.

[30]  F Lau,et al.  Formalized decision-support for cardiovascular intensive care. , 1992, Proceedings. Symposium on Computer Applications in Medical Care.

[31]  Jens Rasmussen,et al.  Diagnostic reasoning in action , 1993, IEEE Trans. Syst. Man Cybern..

[32]  Michel Dojat,et al.  Realistic Model for Temporal Reasoning in Real-Time Patient Monitoring , 1996, Appl. Artif. Intell..

[33]  Jon Inggs,et al.  The first decade , 1996 .

[34]  Ángel Viña,et al.  Guardian: A Prototype Intelligent Agent for Intensive-Care Monitoring , 1994, AAAI.

[35]  P L Miller,et al.  DYNASCENE: an approach to computer-based intelligent cardiovascular monitoring using sequential clinical "scenes". , 1990, Methods of information in medicine.

[36]  Roy Rada,et al.  An object-oriented approach to knowledge representation in a biomedical domain , 1994, Artif. Intell. Medicine.

[37]  P. L. Miller,et al.  Selected Topics in Medical Artificial Intelligence , 1988, Computers and Medicine.

[38]  Enrico W. Coiera,et al.  Intelligent monitoring and control of dynamic physiological systems , 1993, Artif. Intell. Medicine.

[39]  M Dojat,et al.  A knowledge-based system for assisted ventilation of patients in intensive care units , 1992, International journal of clinical monitoring and computing.

[40]  William J. Clancey,et al.  Heuristic Classification , 1986, Artif. Intell..

[41]  Grady Booch,et al.  Object-Oriented Design with Applications , 1990 .

[42]  Adele Goldberg,et al.  SmallTalk 80: The Language , 1989 .

[43]  Lawrence M. Fagan,et al.  A therapy planning architecture that combines decision theory and artificial intelligence techniques. , 1990, Computers and biomedical research, an international journal.

[44]  Marvin Minsky,et al.  A framework for representing knowledge" in the psychology of computer vision , 1975 .

[45]  H Gill,et al.  Adding decision support to a clinical information system. , 1994, Technology and health care : official journal of the European Society for Engineering and Medicine.

[46]  M A Musen,et al.  Dimensions of knowledge sharing and reuse. , 1992, Computers and biomedical research, an international journal.

[47]  Peter F. Patel-Schneider.  Practical, object-based knowledge representation for knowledge-based systems , 1990, Inf. Syst..

[48]  William J. Clancey,et al.  The Epistemology of a Rule-Based Expert System - A Framework for Explanation , 1981, Artif. Intell..

[49]  Francois Pachet,et al.  An extendable knowledge-based system for the control of mechanical ventilation , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[50]  Edward H. Shortlife,et al.  Temporal representation of clinical algorithms using expert-system and database tools. , 1990, Computers and biomedical research, an international journal.

[51]  B. Chandrasekaran,et al.  Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design , 1986, IEEE Expert.

[52]  E. Shortliffe,et al.  Readings in medical artificial intelligence: the first decade , 1984 .

[53]  Bob J. Wielinga,et al.  KADS: a modelling approach to knowledge engineering , 1992 .