Clinical neurophysiology updates, volume 2: Computer-aided electromyography and expert systems edited by J.E. Desmedt, Elsevier, Amsterdam, 1989, 319 pp, $ 161.75

1991 ◽  
Vol 14 (2) ◽  
pp. 187-187
Author(s):  
Sanjeev D. Nandedkar ◽  
Donald B. Sanders
1991 ◽  
Vol 80 (01) ◽  
pp. 34-38 ◽  
Author(s):  
J. Fichefet

AbstractHomœopathy has now come to a turning point. Thanks to Knowledge Base Expert Systems, which appeared recently and are orientated towards drug diagnosis, homœopaths have been made aware of the enormous possibilities that computers can offer them. This applies particularly to the gathering of clinical data and analysis of a collection of clinical files. The purpose of this paper is to summarize what has already been done and suggest what can be done in the future.


1986 ◽  
Vol 18 (7) ◽  
pp. 392-393 ◽  
Author(s):  
Michael A. Rosenman ◽  
John S. Gero ◽  
Peter J. Hutchinson ◽  
Rivka Oxman

1990 ◽  
Vol 45 (8) ◽  
pp. 2661-2667 ◽  
Author(s):  
Shigeharu Kito ◽  
Tadashi Hattori ◽  
Yuichi Murakami

2016 ◽  
Vol 62 (2) ◽  
pp. 217-228 ◽  
Author(s):  
J. Szelka ◽  
Z. Wrona

Abstract Decision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones), the best recognized and successfully used in practice represented by expert systems. The knowledge indispensable for such systems to perform inference is most frequently acquired directly from experts (through a dialogue: a domain expert - a knowledge engineer) and from various source documents. Little is known, however, about the possibility of automating knowledge acquisition in this area and as a result, in practice it is scarcely ever used. It has to be noted that in numerous areas of management more and more attention is paid to the issue of acquiring knowledge from available data. What is known and successfully employed in the practice of aiding the decision-making is the different methods and tools. The paper attempts to select methods for knowledge discovery in data and presents possible ways of representing the acquired knowledge as well as sample tools (including programming ones), allowing for the use of this knowledge in the area under consideration.


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