John Doe - 12-34-56 Lhe patient should receive chemotherapy (PAVE-3A).

Interactive intelligent systems often suffer from a basic conflict between their computationally intensive nature and the need for responsiveness end-user acceptability.

Report 82 38 The Computer and Medical Decision Making: Stanford - KSL Good Advice is Not Enough. Reprinted, with permission, from Engineering in Medicine and Biology Magazine 1,1992. Mailing address: Medical Computer Science, Room TC-117, Division of General Internal Medicine, Stanford University School of Medicine, Stanford, California 94305. Dr. Shortliffe is recipient of Research Career Development Award LM-00048 from the National Library of Medicine. Much of the training of physicians is designed to facilitate optimal, informed clinical decision making.

Medical decision making research has tended to emphasize the generation of optimal decisions, an issue which is central to the development of clinically useful consultation programs. This paper stresses the need to consider other theoretical and practical issues that are pertinent if consultation systems are to be accepted by physicians. Since adequate decision making performance remains an essential component of acceptable systems, the paper suggests c-iteria for selecting clinical problems that may be amenable to short-term implementation using state-of-the-art techniques. Introducticn At the beginning of a third decade of research into the development of computer-based diagnostic aids, it is appropriate for medical computer scientists to assess the strides that have been taken, the barriers that remain, and the optimal strategies for furthering the field in the years ahead. One purpose of this meeting is to take a thoughtful look at medical decision making research and to identify potential solutions to the theoretical and logistical problems that continue to abound [1],[2].

These diverse roles impose several requirements consultation programs has become known as »expert systems upon the system.

Data objects are described G1.ISP is a high-level LISP-based language which is compiled into separately from code which references the objects, making code largely LISP using a know ledge base of object descriptions. I.isp objects and representation-independent, as well as shorter and more objects in VI. representation languages are treated unifomily, this understandable. Type inference is performed when features of an makes program code independent of the data representation used, and object ap accessed, and type information is propagated by the compiler permit., changes of representation without changing code.

Reprinted from the Proceedings of SIGPLAN 1983 Symposium on Programming Languages Issues in Software Systems, Data Abstraction in GLISP by Gordon S. Novak, Jr.

Report 82-33 Welcome to the MRS TUTOR!!! This tutor is designed to introduce you to the syntax and basic database accessing functions of MRS. This document is a transcript of an interaction with the MRS tutor. Reprinted by permission of the author. Funding for this work was provided by ONR Contract N00014-81-K-0004. Representation languages provide a way to store and retrieve facts from a computer. Since English is a grammatically and textually ambiguous language, representation systems use a more formal language to describe the world. The way in which the words or symbols of a language are put together to form phrases and sentences is termed the "syntax" or "grammar" of the language.

Data structures arc described to GEV using the GLISP Structure Description language III; if the user is already programming in GLISP.

This paper describes techniques for representing control knowledge in preaicate calculus. A hybrid system is described in which metarules for diagnostic problem solving and their interpreter (both supplied by the NEOMYCIN program) are expressed in a form of predicate calculus (supplied by MRS). Procedural attachment is used to access and execute the untranslated domain knowledge. A simple deliberation/action loop manages the system at the highest level. There are three metalevels of reasoning.