MYCIN EXPERT SYSTEM

MYCIN:

Historically, the MYCIN system played a major role in stimulating research interest in rule-based expert systems.

MYCIN is an expert system for diagnosing and recommending treatment of bacterial infections of the blood (such as meningitis and bacteremia). It was developed at Stanford University in California, USA, in the 1970s, and has become a template for many similar rule based systems. It is intended to support clinicians in the early diagnosis and treatment of meningitis, which can be fatal if not treated in time.

However, the laboratory tests for these conditions take several days to be completed, so doctors (and therefore MYCIN) have to make decisions with incomplete information associated with medical knowledge. MYCIN incorporated a calculus of uncertainty called certainty factors which seemed (at that time) to fit well with how doctors assessed the impact of evidence on the diagnosis.

This system was able to perform as well as some experts and considerably better than junior doctors. A consultation with MYCIN begins with requests for routine information such as age, medical history and so on, programming to more specific questions as required.

MYCIN’S expertise knowledge lies in the domain of bacterial infections. MYCIN’S pool of knowledge consists of approximately 500 antecedent-consequent rules, implemented in LISP which give MYCIN the ability to recognise about 100 causes of bacterial infections. Physicians usually begin antibiotic treatment for patients who have bacterial infections without knowing exactly which organism is the culprit.

There is no time to wait for definitive laboratory culture evidence, which accumulates too slowly. For the desperately sick, therapy must begin at once, not 2 days after.

This requirement leaves two choices:

i. The physician can either prescribe a broad-spectrum drug which covers all possibilities, or

ii. He can prescribe a better, disease specific drug.

MYCIN helps the physician to prescribe disease-specific drugs. MYCIN informs itself about particular cases by requesting information from the physician about a patient’s symptoms, general condition, history, and laboratory-test results. At each point, the question MYCIN asks is determined by MYCIN’S current hypothesis and the answer to all previous questions. Thus, the questions start as though taken from a checklist, but the questions then vary as evidence builds.

Here is an excerpt from a sample session:

1. What is the patient’s name?

Arun Sehgal

2. Male or Female?

Male

3. Age?

55

4. Have you obtained positive cultures indicating general type?

Yes.

5. What type of infection is it?

Primary bacteria.

6. When did symptoms first appear?

May 5, 2006

7. Let’s call the most recent positive culture C1. From what site was C1 taken?

From the blood.

8. When?

May 9, 2006

9. Let’s call the first significant organism from this culture U1. Do you know the identity of U1?

No.

10. Is U1 a rod or a coccus or something else?

Rod.

11. What in the gram stain of U1?

Gram-negative.

12. Have there been positive cultures from sites which are not associated with the infections about which you are seeking advice?

No.

13. Did U1 grow aerobically?

Yes.

When MYCIN is satisfied that it has a reasonably good grasp of the situation, MYCIN announces its diagnosis:

My recommendation will be based on the opinion that the identity of U1 may be:

1. Pseudomonas-aeruginosa

2. Klebsiella-pneumonise.

3. E.coli

4. Bacteroides-fragilis.

5. Enterobacter.

6. Proteus-nonmirabilis.

After asking a few more questions about the patient, MYCIN announces its recommendation:

1. On a scale of 0 to 4, where the higher number indicates greater severity, how would you rate the patient’s degree of sickness?

2. Does the patient have a clinically significant allergic reaction to any antimicrobial agent?

3. How much does the patient weigh?

4. My first recommendation is as follows: to cover for items 1, 2, 3, 5 and 6, give gentamycin using a dose of 119 mg (1.7 mg/kg) q8h IV [or IM] for 10 days. Modify dose in renal failure. Also, to cover for item 4, give clindamycin using a dose of 595 mg (8.5 mg/kg) q6th IV [or IM] for 14 days. If diarrhea or other gastrointestinal symptoms develop, check for pseudomembranous colitis.

It has the following organisational features:

i. Knowledge Representation:

In the form of production rules implemented in LISP. K.B. is of the form – If condition, and …. and condition hold then draw conclusion, and …. and conclusion encoded in the data structure of LISP programming.

ii. Reasoning:

Backward chaining, and forward reasoning uses certainty factors to reason with uncertain information. MYCIN uses backward chaining to discover what organisms where present. Then it uses forward chaining to reason from the organism to a treatment regime.

iii. Heuristics:

When the general category of infection has been established, MYCIN examines each candidate diagnosis in a depth-first manner. Heuristics are used to limit the search, including checking all premises of a possible rule to see if anyone of these is known to be false.

iv. Dialogue/Explanation:

The dialogue is computer controlled, with MYCIN driving the consultation through asking questions. Explanations are generated by tracing back through the rules which have been fired. Both “how? ” and “why? ” explanation are supported.