Artificial Intelligence in Medicine: Expert Systems

177 Pages·1990·3.98 MB·English

by  Marius Fieschi (auth.)

Artificial Intelligence in Medicine
Artificial Intelligence in
Medicine
Expert systems
M. Fieschi
Faculty of Medicine
University of Marseilles
Translated by D. Cramp
Royal Free Hospital
London
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
Original French language edition (Intelligence Artificielle en
Medecine des Systemes experts)
© Masson, Editeur, Paris, 1984
English translation published 1990
© 1990 Springer Science+Business Media Dordrecht
Originally published by Chapman and Hall in 1990
Softcover reprint of the hardcover 1s t edition 1990
Typeset in 10/12 Palatino by
Best-set Typesetter Limited, Hong Kong
ISBN 978-0-412-33000-1
All rights reserved. No part of this publication may be
reproduced or transmitted, in any form or by any means,
electronic, mechanical, photocopying, recording or
otherwise, or stored in any retrieval system of any nature,
without the written permission of the copyright holder and
the publisher, application for which shall be made to the
publisher.
British Library Cataloguing in Publication Data
Fieschi, M.
Artificial intelligence in medicine Expert systems.
1. Medicine. Applications of expert systems
I. Title
610' .28'5633
ISBN 978-0-412-33000-1
Library of Congress Cataloging-in-Publication Data
Fieschi, M. (Marius)
[Intelligence artificielle en medecine des systemes
experts. English]
Artificial intelligence in medicine: expert systems /
M. Fieschi; translated by D. Cramp.
p. cm.
Translation of: Intelligence artificielle en medecine des
systemes experts.
Includes bibliographical references.
ISBN 978-0-412-33000-1 ISBN 978-1-4899-3428-4 (eBook)
DOI 10.1007/978-1-4899-3428-4
1. Artificial intelligence-Medical applications.
2. Expert systems (Computer science) 3. Medicine
Decision making-Data processing. I. Title.
R859.7.A78F5413 1990
610' .285'63-dc20 89-71255
CIP
Contents
Preface vii
Foreword viii
Introduction xii
PART ONE Expert Systems in Medicine 1
1. Medical reasoning and artificial intelligence:
general presentation of the problem 3
2. Representation and use of the knowledge 11
2.1 Production systems 12
2.2 Semantic networks 25
2.3 Frames 31
2.4 Other systems 41
PART TWO Study of an Expert System 49
3. The SPHINX system 51
3.1 Testing the prototype 52
3.2 General presentation of the system 53
3.3 Entities from the field of medical discourse 54
3.4 Production and use of the entities in the dialogue,
MEDIUM 59
3.5 EXPERT: organization and use of the knowledge 63
3.6 Discussion 88
4. Examples of applications 92
4.1 Application to the diagnostic aid for jaundice 92
4.2 Application to therapeutic aid in the treatment
of diabetes 99
4.3 Discussion 105
5. The SPHINX system environment 106
5.1 The COBASE program 107
5.2 The ARIANE program 109
PART THREE Validation 111
6. Validation of the expert systems 113
6.1 The interface Sub-system 115
6.2 The inference Sub-system 116
6.3 Control of the knowledge base 118
6.4 Consensus, precision of advice, performance 118
7. A crucial problem: validation of the knowledge base 120
7.1 Methods 120
7.2 Some noteworthy examples 121
7.3 Difficulties of objective valuation 123
7.4 Comments on knowledge base validation and
expert consensus 127
8. Validation of a SPHINX knowledge base:
some supplementary elements 128
8.1 The protocol 128
8.2 The results 131
8.3 Sensitivity study 135
Appendix 1 Representation and use of knowledge:
symbolic logic 136
Appendix 2 Representation and use of knowledge:
fuzzy sets and fuzzy logic 145
Appendix 3 LISP coding of the MYCIN rules 153
Appendix 4 Bayes' theorem and credibility factors 154
Appendix 5 Other medical systems which employ
artificial intelligence methods 158
References 159
Index 165
Preface
Expert systems constitute a research area which is currently expanding.
This book is based largely on work undertaken for my doctoral thesis
and attempts to set out in readily understood language the different
methods of knowledge representation used in different systems. How
ever, since the field for applications is enormous and touches on many
disciplines (engineering science, computing, geology, medicine etc.)
only those systems with medical applications are presented. The second
part of this book is devoted to detailed discussion of one expert system
developed in this department: SPHINX.
I wish to thank all those who have given me their support, their
criticisms and suggestions: Dominique Fieschi, Michel Joubert, Genevieve
Botti, Michel Roux, Jean-Louis Lauriere, as well as the CNRS which
supported the ATP Expert Systems Group with an individual grant.
Marius Fieschi
Foreword
This work deals with 'Expert Systems' in the realm of medicine. The
phrase 'Expert System' describes an information system not only in
terms of its content but also in terms of its application. As with all
generic terms, it is condensed to the point where the meaning cannot be
guessed from simply reading it.
It concerns systems processing knowledge and behaviour in ways
close to those of a human expert. In the field of medicine this expert
would be the consultant or specialist to whom a family practitioner
refers a 'case' which he is unable to diagnose. The study of expert
systems is a branch of computer science called artificial intelligence.
Artificial intelligence, a strange phrase in which the two words taken
separately conjure up opposite meanings. Intelligence seems to us to be
intimately associated with human behaviour. The idea of 'artificial', on
the other hand, conjures up the idea of objects characteristically not
natural but 'man-made'. To call 'artificial' a prime component of human
nature seems a paradox. This term is badly chosen, particularly as the
aim of artificial intelligence systems is to represent behaviour com
parable to human behaviour.
To gain a better grasp of the problems involved in applying artificial
intelligence in medicine, let us trace the origin of the word 'intelligence'.
It is derived from the Latin 'intelligentia' which is in turn derived from
the verb 'intelligere': to understand. The dictionary gives the following
definition of intelligence: 'The intellect in so far as it understands, in so
far as it thinks; ability to understand and to understand.'
According to Larousse, intelligence is the: 'ability to understand, to
make sense. The ability to adapt to a situation, to choose according to
circumstances'. Whether included under the heading 'Psychology' or
'Logic' in text books of philosophy, several established ideas concerning
the definition and analysis of intelligence are to be found. Most authors
attribute several properties to intelligence: knowledge, understanding,
memory.
Certain authors have adopted a point of view which is of particular
interest to us; namely, the ability to grasp ideas which do not depend on
experience. This suggests the existence of a process of reasoning which
FOREWORD ix
is independent of knowledge and leads to other complex processes like
abstraction (conceptualization of observed facts) and generalization
(finding a shape or properties common to several concepts) to achieve a
more general idea.
The early accomplishments of expert systems (information systems
showing intelligent behaviour and containing large quantities of human
knowledge, often elicited) have shown the difference between know
ledge and reasoning, a distinction barely considered by philosophers.
From this new perspective, knowledge comprises:
1. Elementary facts (or those considered as such). This is the establish
ment of the existence of specific facts: cough, the blood glucose level,
the existence of a geological stratum, a word of a language.
2. The connection between basic facts which allow a complete descrip
tion of the elementary facts to describe their properties and the
associations between them.
To make use of this knowledge, or in other words to infer the existence
of new facts or new properties, it is necessary to set up one or more
practical techniques. The best known of these is the 'Modus Ponens': a
classical term in mathematical logic which is met again in cognitive
psychology. It is an elementary technique which if repeated very many
times will lead to the desired result. The program which carries out this
elementary technique is called the 'inference engine'.
Whatever the practical technique used, the introduction of expert
systems compels one to formalize one's thinking and to analyse and
express it more efficiently. Information thus 'enhanced' and better ex
pressed becomes more efficient not only for information systems, but for
man himself who in this way 'knows better what he knows and how he
knows it.' The change in the attitude of mind of experts who work in
this field is very clear-cut. The writing, the extraction of information, its
clarity of expression, are indispensable steps in the production of expert
systems, which thus involves a definite educational perspective and also
necessitates formulation of hypotheses which would not have been
envisaged in other circumstances.
Areas for application of expert systems in medicine are numerous and
at the present time could include:
1. The diagnostic aid: where the system plays the role of the consultant.
2. The therapeutic aid: this area of application will be much more in
demand. For proof of this one need only consider the numerous
enquiries which crop up among medical practitioners, many of
whom are uncertain how to prescribe appropriately for a given diag-
x FOREWORD
nosis, and how to adjust the prescription to the exact circumstances
of the patient; also their need to know when the drug is contra
indicated.
3. Teaching: in order to teach a topic it is necessary to be conversant
with it. An expert system teaching-aid must therefore of necessity
contain a sub-system helping in diagnosis and/or therapy and should
also adapt to the level of knowledge and 'intelligence' of its user.
4. Research aid: something about this has been said when indicating
changes taking place amongst clinicians. These changes constitute
an advance in the standard concept of research; moreover, expert
systems can work out hypotheses, known or unknown. In this last
case, these hypotheses become research objectives. Some actual
examples have already been presented.
5. Biological and medical engineering: the 'automated' interpretation of
functional examinations and physiological signals in the context of
the specific circumstances of the patient.
The principal problems actually raised by the formulation and use of
these systems are:
1. Knowledge representation: to adopt such structures that are not only
general but also powerful and easy to use. The quality and theoretical
backup of the inference engine including propositional logic is already
well tried as to some extent is first-order logic.
2. The man-machine interface: in natural language, convenient to use
though complex to analyse and appreciative of data processing
resources.
3. The choice of certainty in reasoning and intervention of approximate
reasoning. In this last case it is necessary to introduce numerical
techniques or use the symbolic calculus. Reasoning by analogy using
the calculus may be the 'solution' for dealing correctly with an
uncertainty .
Such is the fascinating area dealt with in Dr Fieschi's book which is
based on his doctoral thesis, in which he analyses the characteristics
of the principal existing medical expert systems. It is, however, an
advanced project because it also describes the system created and
developed by the author based on first order logic. The work testifies to
the vitality of the research within this area and also to the value of the
author's achievement.
Artificial intelligence in medicine is going to take a very important
place in the science of medical informatics.
This preface cannot be concluded without drawing attention to the