MYCIN System

An MYCIN System is an expert system that was developed in the 70s to help physicians treat blood infections, prior to the arrival of comprehensive blood-test results.

Context:
- It kept the rules (or embodied knowledge) separate from the inference engine that applied the rules (Unlike DENDRAL).
- It represented its knowledge as a set of IF-THEN rules (LISP expressions) with certainty factors and used basic backward chaining inference to reach its goal state.
- It elucidated the problem of mixing domain knowledge with problem solving knowledge.
- It was never used routinely by physicians.
- It was developed at Stanford from 1972 to 1980.
Example(s):
- an EMYCIN System,
- a TMYCIN System.
- …
Counter-Example(s):
- DENDRAL System,
- Kira Systems.
See: Biomedicine Domain, Computational Biology, AI.

References

(Wikibooks, 2016) ⇒ (2016). Expert Systems/MYCIN. Wikibooks, The Free Textbook Project. Retrieved 21:38, February 3, 2019.
- QUOTE: Mycin was an early expert system developed over five or six years in the early 1970s at Stanford University; it was written in Lisp, by Edward Shortliffe under the direction of Bruce Buchanan and others; it derived from the earlier Dendral expert system, but considerably modified and extended the basic Dendral software. This computer system was designed to diagnose infectious blood diseases and recommend antibiotics, with the dosage andjusted for patient's body weight — the name derived from the antibiotics themselves, as many antibiotics have the suffix "-mycin".

(Buchanan & Shortliffe, 1977) ⇒ Bruce G. Buchanan, and Edward H. Shortliffe (1977). Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project.
- QUOTE: Artificial intelligence, or AI, is largely an experimental science — at least as much progress has been made by building and analyzing programs as by examining theoretical questions. MYCIN is one of several well-known programs that embody some intelligence and provide data on the extent to which intelligent behavior can be programmed. As with other AI programs, its development was slow and not always in a forward direction. But we feel we learned some useful lessons in the course of nearly a decade of work on MYCIN and related programs. In this book we share the results of many experiments performed in that time, and we try to paint a coherent picture of the work. The book is intended to be a critical analysis of several pieces of related research, performed by a large number of scientists. We believe that the whole field of AI will benefit from such attempts to take a detailed retrospective look at experiments, for in this way the scientific foundations of the field will gradually be defined. It is for all these reasons that we have prepared this analysis of the MYCIN experiments