MYCIN was first developed at Stanford University in California in 1972. MYCIN would make an effort to make a diagnosis based on patient reports of symptoms and the outcomes of diagnostic procedures. 

MYCIN worked with a knowledge base of about 600 rules and a simple inference engine. It would ask the doctor running the program a long list of easy yes/no or text-based questions. MYCIN ranked possible culprit bacteria from high to low based on likelihood, confidence, reasoning, and drug treatment.

Certainty factors

MYCIN started discussing how to use its "certainty factors," which are ad hoc but based on good ideas. The people who made MYCIN did studies that showed how little changes in the uncertainty metrics of individual rules affected its performance. It suggests that the system's power came from how it represented and exploited knowledge rather than its numerical uncertainty model. Some people thought that standard Bayesian statistics should have been able to be used. The people who made MYCIN said this would require either making unrealistic assumptions about independent probabilities or asking experts to give figures for many conditional probabilities.

Flexible design

Studies done in the future showed that the certainty factor model could be understood probabilistically and pointed out problems with such a model's claims. The system's flexible design would work very well and lead to the creation of graphical models like Bayesian networks.

Evaluation

MYCIN was never used in the real world. It wasn't because it needed to work better. Some observers raised moral and legal questions about using computers in medicine, like who would be responsible if the system made a wrong judgment. However, the state of system integration tools, especially when MYCIN was made, was the biggest problem and the main reason it was used sparingly. MYCIN was a stand-alone system that asked the user to type in answers to questions about a patient. Before personal computers were made, the program ran on an extensive time-shared system that could be reached through the early Internet (ARPANet).

Results

In research done at Stanford Medical School, eight independent specialists gave the MYCIN treatment plan an acceptability rating of 65%, about the same as the 42.5% to 62.5% rate provided by five faculty members. People often point to this study to show that even experts can disagree about how to treat someone when there is no "gold standard" for the proper treatment.

Conclusion

The most crucial thing MYCIN did was show how powerful its method of representation and reasoning was. Since MYCIN introduced the technique, rule-based systems were built in many fields other than medicine. In the 1980s, "shells" for expert systems were created, such as E-MYCIN, which was based on MYCIN and was later replaced by Knowledge Engineering Environment (KEE). These "shells" helped build expert systems for various uses. 

Furthermore, one problem during the development of MYCIN and other complex expert systems was getting human experts in the relevant areas to put their knowledge into the rule base so that the inference engine could use it.

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