Artificial Intelligence in Medicine 5 (1993) 393-394 Ekvier 393

ARmED 215

Guest editor’s introduction

Predicate logic essentially is a language for expressing knowledge concerning objects

and relations between these objects in a given domain. Because many problems can be cast naturally in such terms, there is at first sight no reason why logic should not be a suitable language for the representation and solution of medical problems. However, with the exception of the application of PROLOG as a programming language for the implementation

of a number of medical AI applications, logical languages have not been particularly popular in the medical AI community. Only in recent years, some research is being focussed on using logic in medical problem solving.

This special issue of Artificial Intelligence in Medicine is devoted to research concerning the use of logical languages and systems in building medical applications. This research includes two aspects:

(1) the development of restricted and special-purpose logics to comply with the nature of the medical domain, and

(2) the application of modem techniques developed in the field of logic programming to the solution of medical problems.

In the first paper, The representation of medical reasoning models in resolution-based theorem provers by the guest-editor, it is shown that different medical problems, more in particular heuristic diagnostic reasoning, anatomical reasoning and causal reasoning, give rise to differ- ent syntactical restrictions on full first-order predicate logic. It is also shown that resolution- based theorem-proving methods offer a good start for the implementation of logic-based medical expert systems.

The second paper, Symbolic decision support in medical care by J. Huang, J. Fox, C.

Gordon and A. Jackson-Smale, describes a prototype system for medical decision support, based on techniques from logic. The central themes of the paper are the use of (layered) meta- level representation techniques and the augmentation of logical deduction with a symbolic weighting scheme for dealing with uncertain and incomplete information, called the ‘logic of argumentation’.

The third paper, Logic-based integrity constraints and the design of dental prostheses by P. Hammond, J.C. Davenport and F.J. Fitzpatrick, discusses the application of techniques from the field of logic programming to the design of dental prostheses, with some emphasis on the use of logical integrity constraints in the style of the work of R.A. Kowalski. It discusses the implementation of a prototype program in PROLOG that conforms to those principles. This program is an interesting demonstration of the power of modem logic programming techniques for building expert systems.

The final paper, A constraint logicprogrammingfiamework for constructing DNA restric-

093X3657/93/$06.00 @ 1993 - Elsevier Science Publishers B.V. All rights reserved

394 Guest editor’s introduction

tion maps by R.H.C. Yap, discusses the declarative use of equality and inequality constraints on the field of real numbers to the problem of DNA analysis within a logic programming framework. The ability to use equality and inequality in a declaratively correct way, as offered by constraint logic programming language such as CLP(R), may be viewed as an important step in the effort of moving away from the procedural aspects of PROLOG. The paper demonstrates that constraint logic programming offers an elegant and flexible approach to the problem of DNA analysis

In summary, these four papers provide the reader with a state-of-the-art account of possible applications of logical techniques to the field of medicine. The research reported in this spe- cial issue convincingly shows that the techniques offered by modern logic-based automated reasoning technology deserve a place among the useful tools in the computer scientist’s toolkit employed in solving medical problems.

Peter Lucas Department of Computer Science

University of Utrecht