This document discusses the development and testing of the MYCIN expert system. MYCIN was developed in 1976 at Stanford University to diagnose and recommend treatment for bacterial infections. It was tested against physicians and found to be as or more accurate in its diagnoses and treatment recommendations. However, MYCIN was never fully implemented in clinical practice due to legal liability concerns if it provided incorrect diagnoses.

2. •In 1965 DENDRAL was
used in expert system
•MYCIN was developed in
1976

3. WHY MYCIN
 Disease diagnosis and therapy selection
 Advise for non expert physicians with time
consideration and incomplete evidence as
 Bacterial infections of the blood
 Extended to other elements

4. PROBLEM BEFORE MYCIN
• ROBERTS AND VISCONTI:-
 Only 13% patients are treated rationally
 66% are being given irrational treatment
 21% are being given questionable treatment
• IRRATIONAL MEANS, FOR EXAMPLE: Using a contra-indicated combination
 Using the wrong agent for a specific organisms
 Not taking the required culture

5. DEVELOPMENT OF MYCIN
• Developed by ADWARD SHORTLIFFE in 1976
a STANFORD UNIVERSITY in the artificial intelligence
in medicine group
• First system that was implemented into the medical
field

6. HOW MYCIN WAS TESTED FOR
ACCURACY
• 10 patients for a particular disease were chosen
• Their information was sent to 8 physicians and MYCIN
• All then came up with recommended treatment
• Those recommendations along with what the patient
actually received as treatment was sent to 8
unidentified specialists

7. WHO WON FROM THE TEST
• MYCIN won the test
• MYCIN received the highest score as for as
accuracy and effectiveness of diagnosis

8. STAGES IN DAIGNOSIS AND
TREATMENT
• Decide if there is significant infection
• Identify the causing organism(s) by clinical and
laboratory evidence
• Decide what antibiotic agent the organisms are
sensitive to
• Prescribe the optimal drug combination for particular
case

9. RESULTS
 Never implemented for routine clinical use
 Shown to be competent by panels of experts even in
case where experts themselves disagreed on
conclusions
 Key contributions
 Reuse of production rules( expansion knowledge aquision )

10. PROBLEMS
• If the system gives an incorrect diagnosis, who is
to be blamed or sued
• Physicians rely to heavily on system instead of
consulting other experts

11. Resources
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Wikipedia Page
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Building Expert Systems in Prolog
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Available at: http://www.amzi.com/ExpertSystemsInProlog/xsipfrtop.htm
Artificial Intelligence - A modern Approach by Stuart Rassell, Peter
Norvig
PC AI – Expert Systems
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Available at: http://en.wikipedia.org/wiki/Expert_system
Available at: http://www.pcai.com/web/ai_info/expert_systems.html
VisiRule Web Demos (A simple example):
http://www.lpa.co.uk/vrs_dem.htm