Mycin
MYCIN was an early
Method
MYCIN operated using a fairly simple inference engine and a knowledge base of ~600 rules. It would query the physician running the program via a long series of simple yes/no or textual questions. At the end, it provided a list of possible culprit bacteria ranked from high to low based on the probability of each diagnosis, its confidence in each diagnosis' probability, the reasoning behind each diagnosis (that is, MYCIN would also list the questions and rules which led it to rank a diagnosis a particular way), and its recommended course of drug treatment.
MYCIN sparked debate about the use of its
Subsequent studies later showed that the certainty factor model could indeed be interpreted in a probabilistic sense, and highlighted problems with the implied assumptions of such a model. However the modular structure of the system would prove very successful, leading to the development of graphical models such as Bayesian networks.[3]
Evidence combination
In MYCIN it was possible that two or more rules might draw conclusions about a parameter with different weights of evidence. For example, one rule may conclude that the organism in question is E. Coli with a certainty of 0.8 whilst another concludes that it is E. Coli with a certainty of 0.5 or even -0.8. In the event the certainty is less than zero the evidence is actually against the hypothesis. In order to calculate the certainty factor MYCIN combined these weights using the formula below to yield a single certainty factor:
Where X and Y are the certainty factors.[4] This formula can be applied more than once if more than two rules draw conclusions about the same parameter. It is commutative, so it does not matter in which order the weights were combined.
Results
Research conducted at the
Practical use
MYCIN was never actually used in practice. This wasn't because of any weakness in its performance. Some observers raised ethical and legal issues related to the use of computers in medicine, regarding the responsibility of the physicians in case the system gave wrong diagnosis.
MYCIN's greatest influence was accordingly its demonstration of the power of its representation and reasoning approach. Rule-based systems in many non-medical domains were developed in the years that followed MYCIN's introduction of the approach. In the 1980s, expert system "shells" were introduced (including one based on MYCIN, known as E-MYCIN (followed by
See also
References
- S2CID 118063112.
- ISBN 978-0-201-10172-0.
- .
- ISBN 978-0-201-87686-4.
- PMID 480542.
- ^ Trivedi, M. C. (2014). A Classical Approach to Artificial Intelligence (2nd ed.). Van Haren Publishing. p. 331
- The AI Business: The commercial uses of artificial intelligence, ed. ISBN 0-262-23117-4.
External links
- Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project -(edited by Bruce G. Buchanan and Edward H. Shortlife; ebook version)
- TMYCIN, system based on MYCIN
- "Mycin Expert System: A Ruby Implementation" (at the Web Archive).
- "MYCIN: A Quick Case Study"
- " SOME EXPERT SYSTEM NEED COMMON SENSE" -(by John McCarthy)
- "Expert Systems"