"Learning", the incorporation of additional knowledge into expert systems, ranges from human data entry (learning by being told), to data gathering (learning by observing), to full-fledged theory formation (learning by discovery). One important kind of learning is the compiling of descriptive meta-knowledge into strategic form, recasting it into a form in which it can be evaluated efficiently. Much of what we earlier called strategic meta-knowledge may be seen to be operationalized "caches" of descriptive or systemic meta-knowledge. For instance, R9 and R10 can be converted from systemic to strategic form by slight rewordings of their actions.

Search 4. Methods for assigning credit and blame--obtaining a local Performance Standard

This manual describes a domain-independent system, called EMYCIN, for constructing one class of expert computer programs: rule-based consultants. The resulting programs use knowledge specific to a problem domain to provide consultative advice to a client. The system-building tool, EMYCIN, is based on the domain-independent core of the MYCIN program. Domain kno,./ledge is represented in EMYCIN systems primarily as production rules, which are applied by a goal-directed backwardchaining control structure. Rules and consultation data may have associated measures of certainty, and incomplete data entry is allowed. The system includes an explanation facility that can display the line of reasoning followed by the consultation program, and answer questions from the client about the contents of its knowledge base. To aid the system designer in producing a knowledge base for a domain quickly and accurately, EMYCIN provides the following features: (1) a terse.

This paper presents an "expert system" devised to aid organic chemists in determining the structure (i.e. the arrangement of atoms and bonds) of newly isolated, naturally occurring compounds. The system exploits a data base of rules for analyzing.013 C nuclear magnetic resonance spectra" [2. 13 C spectroscopy is a relatively new technique; only in the last ten years, at most, has this analytic approach been practical. Currently, no general interpretive schemes exist for thoroughly analyzing 13C spectra. A few limited classes of compounds have been investigated in detail, and highly specific schemes for interpreting their 13C spectra have been developed. The only generally applicabl- "interpretation rules" rely on correlation J of spectral and substructural features.

We describe an oncology protocol management system, named ONCOCIN, that is designed to assist physicians in the treatment of cancer patients. The system is a set of related programs, one of which is a rule-based reasoner that encompasses the necessary knowledge of cancer chemotherapy. Representation and control techniques are dizcussed, and ONCOCIN is contra7ted with:qstems that could be built using EMYCIN. Of particular Interest is the need to provide ONCOCIN with an interface that will make the system acceptable to oncologists.

We describe a program for verifying that a set of rules in an expert system comprehensively spans the knowledge of a specialized domain. The program has been devised and tested within the context of the ONCOCIN System, s rule-- based consultant for clinical oncology. The stylized format of ONCOCTN's rules has allowed the automatic detection of a number of common errors as the knowledge base has been developed. This capability suggests a general mecharism for correcting most problems with knowledge base completeness and consistency before they can cause performance errors.

The Key idea is to represent explicitly and separately: a A. The limitations of MYCIN for application to teaching domain-independent diagnostic strategy in the form of meta-rules,

To be presented at the Eighteenth Annual Meeting of the Drug Information Association, Kansas City, Missouri, June 16, 1982. Edward H. Shortliffe, MD, PhD Assistant Professor of Medicine and Computer Science Heuristic Programming Project Department of Medicine Stanford University School of Medicine Stanford, California 94305 To be presented at the Eighteenth Annual Meeting of the Drug Information Association Kansas City, Missouri 16 June 1982 ABSTRACT The trend towards increased use of computer-based symbolic reasoning techniques for clinical decision making programs stems from the dual goals of improving the performance and increasing the acceptance of such systems. This talk will summarize the design considerations that have encouraged some recent investigators to turn to artificial intelligence techniques when'bJllding consultation systems. Some of the recent experimental consultation systems are less concerned with reaching correct diagnoses than with advising physicians un optimal treatment strategies for patients with known serious ..',Iscases. Examples for discussion will be drawn from (1) the MYCIN system, a consultation program to advise physicians on the selection of antimicrobials for patients with bacteremia or meningitis, and (2) ONCOCIN, a recently developed program for advising oncologists on therapy adjustment in the manarement of patients enrolled in cancer chemotherapy protocols.

This memo contains two papers that deal with medical computing. The first, written for a book on cybernetics and society, examines the range of medical computing systems, plus some of the logistical and human engineering challenges limiting their utility or acceptance. It addresses five recurring themes that characterize the introduction of medical computing systems: 1) the need for the proposed application, 2) the system users, 3) the logistics of system introduction, 4) the required computational techniques, and 5) the required technological resources. In the context of these topics, suggestions are offered for long-range research and resource policies that are appropriate for assuring the development of practical clinical computing. The second paper, presented at a meeting on artificial intelligence in May 1980, takes a more detailed look at the reasons that medical computing systems have had a limited impact on clinical medicine. When one examines the most common reasons for poor acceptance of such systems, the potential relevance of artificial intelligence techniques becomes evident. The paper proposes design criteria for clinical computing systems and demonstrates their relationship to current research in knowledge engineering. The MYCIN System is used to illustrate the ways in which one research group has responded to the design criteria cited.

This paper briefly outlines the difference between Branching on the bas of response was the first step coward traditional instructional programs and MAI.