People's certainty of the past is D follows from A. B. and C. It may be that A. B. and C, limited by the fidelity of the devices that record it, their though certain, suggest but do not confirm D. in which case knowledge of the present is always incomplete, and their the number associated with D might be less than the 1.0 that knowledge of the future is but speculation. Even though usually represents certainty in such systems. If A. B. or C nothing is certain, people behave as if almost nothing is are uncertain, then the number associated with D is modified uncertain. They are adept at discounting uncertainty -- to account for the uncertainty of its premises. These numbers making it go away. This article discusses how Al programs are given different names by different authors; we refer might be made similarly adept.

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

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.

Theorem Proving Vision Robotics Information Processing Psychology Learning and Inductive Inference Planning and Related Problem-solving Techniques A. Overview There are two main area.

It is noted that no one method is best with a view to the potential role of automated decision for all applications. However, emphasis is given to the limitations of early work that have made artificial intelligence techniques and knowledge aids in that domain 1611.

A clinical investigator graphical capabilities which can plot specific parameters for a keeping the records of his study patients on such a system can patient over time 1126]. However, it is in the analysis of stored use the program's statistical capabilities for data analysis.

In this paper we examine the selection.

Almost one-half of the total cost of drugs spent in treating hospitalized patients is spend on antibiotics (1,2), and a significant part of this therapy is associated with serious misuse (2,3,4,5). One problem involves incorrect selection of a therapeutic regimen [4], while another involves the incorrect decision to administer any antibiotic (2,4,5). For example, one recent study concluded that one out of every four people in the United States was given penicillin during a recent year, and nearly 907. of these preL,criptions were oahccessary (6).

How could one represent with a single prototype the class of figures which have an even number of disconnected parts?

How could one represent with a single prototype the class of figures which have an even number of disconnected parts?