Mycin

1
Mycin

• CIS 479/579
• Bruce R. Maxim
• UM-Dearborn

2
Mycin

• Task
• Prescribe drug regimen for infectious virus and
  diseases
• Rationale
• It was estimated that in 1972 physicians were
  over prescribing antibiotics by a factor of 10-20
  times too much
• Costly and breeds strains of bacteria resistant
  to treatment

3
Design Parameter

• Program must be competent easy to use
• Must handle a large, changing body of knowledge
• Interact with human users
• Must take time into account
• Work with incomplete or uncertain information

4
System Components

• Consultation system
• Asks questions
• Draws conclusions
• Gives advice
• Explanation system
• Translates rule to English before display
• Rule acquisition/modification system

5
Rule Grammar

• ltrules.
• ltpremisegt ltactiongt
• ltpremisegt
• (AND ltconditiongt ltconditiongt)
• ltconditiongt
• (ltpredicategt ltcontextgt ltparametergt ltvaluegt)
  
• (OR ltconditiongt ltconditiongt)
• ltactiongt
• ltconclusiongt ltinstructiongt

6
Lisp Rule

• Premise
• (and (same cntxt gram gramneg)
• (same cntxt morph rod)
• (same cntxt air aerobic))
• Action
• (conclude cntxt class enterobacteriacae tally 0.8)

7
English Rule

• IF strain of org is gramneg and
• morphology of org is rod and
• aerobicity of org is aerobic
• THEN
• there is strongly suggestive evidence
• (0.8) that the class of org is
• enterobacteriacae

8
Static Data Structures

• Simple lists
• enumerate organisms and sterile sites known to
  system
• Knowledge tables
• contain clinical parameters and their values
  under various circumstances
• Classification system
• clinical parameters according the contexts in
  which they apply

9
Dynamic Data Structures

• Context tree
• serves to organize information relating to a
  particular patient
• used to structure clinical problem and relate
  contexts to one another
• rules are related to the context tree (although
  the rules themselves are not organized into
  either a decision tree or inference network)

10
Working Memory

• Knowledge is represented using AOV triples with
  certainty factors
• (attribute object value certainty)
• (IDENT ORG1 ENTEROBACTERIACAE 0.8)

11
Control Structure

• Backward chaining
• helps to keep it focuses
• facilitates backward reasoning from top level
  goal for all queries

12
Inference Strategy

• Subgoals are generalized (i.e. match with
  variables) when possible
• All applicable rules are evaluated before
  reaching a decision
• Facts with certainities between 0.2 and 0.2 are
  treated as unknown
• Mycin asks for lab for some facts before
  attempting a deduction
• A list of rules that fail under the current
  context is maintained to avoid re-evaluation
• Premises are evaluated based on known fact before
  search is allowed

13
Goal Rule

• IF
• there is an org requiring therapy and
• consideration has been given to possibilty of
  other orgs requiring therapy
• THEN
• compile a list of possible therapies and
• select the best alternative from list

14
Consultation Procedure

• Create a patient context as the top level node in
  the context tree
• Attempt to apply the goal rule to this particular
  patient context
• Context tree is fleshed out in an effort to
  accumulate evidence from user query or inference
• Each node contains accumulated evidence including
  lab data to allow alternation between question
  selection and rule invocation

15
Mutually Recursive Procedures

• Monitor
• attempts to evaluate premise of current rule
• if it fails rule is discarded and next rule from
  list is examined (restricted by context)
• Findout
• gathers evidence for and against rule premise
• if question can be asked control returns to
  Monitor with answer
• if no question new list of rules to determine
  truth of rule premise is returned to Monitor

16
Mycin Rules

• Had 200 rules in 1976
• Meta-rules
• rule pruners similar to alpha/beta cutoffs
• rules to reorder relevant domain rules
• general (domain free) problem solving heuristics
• some forward (antecedent) reasoning to cut stupid
  questions (i.e. skip pregnancy questions for
  males)

17
Explanation System

• Can display rule being invoked at any point in
  consultation
• Record rule invocation and associates them with
  questions asked and rules invoked
• Use rule index to retrieve particular rules in
  answer to questions
• Why and how questions answered using goal tree

18
Rule Acquisition System

• Domain experts allowed to enter and change rules
• Rules translated to Lisp and rule numbers added
  to Look-ahead and Updated-by lists
• Does not catch contractions and inconsistencies
  in large rule-bases

19
Evaluation

• 1974
• Panel of 5 experts approve 72 of Mycins
  recommendations for 15 patients
• 1976
• 8 experts (5 faculty, 1 resident, 1 med student,
  1 research fellow) made drug recommendations for
  10 patients
• Mycin had best match (52) with actual drug
  recommendations used by attending physician

20
Summary

• Mycin combines the advantages of general
  rule-based system with the advantages of an
  inexact reasoning system
• Mycin has not addressed
• how to convert from human terms to certainties
• how to normalize across different peoples
• how far to propagate certainty factor changes
  based on new evidence
• how to provide feedback to database to improve
  certainty factor accuracy

21
Emycin

• One of the first expert systems shells
• Basically Mycin with its domain specific
  knowledge removed
• Uses backward chaining with Mycins antecedent
  rule processing
• Includes some tools to allow KEs to debug large
  systems

22
Monitoring Behavior

• Explain
• essentially a trace of rules involved to make
  inferences
• Test
• allows comparison of current run with stored run
  and prints list of discprepencies
• Review
• allows expert to examine system conclusions on
  stored cases

23
Sacon

• Emycin had an English-like rule language called
  Sacon
• IF composition list of methods and
• error lt 5 and
• nd-cycles gt 0.5 and
• THEN
• ss-stree fatique

24
Emycin Weaknesses

• Emycin approach is only useful in domain where
  task is to provide consultative advice
• Use of certainty factors smacks of probability
  theory without having assurance of independence
• Certainty factors may not be valid in every
  domain
• Approach was derived from Mycin which was
  implemented to be very domain specific

25
Teiresias

• Created to do knowledge acquisition and truth
  maintenance for Mycin
• Designed to identify
• gaps in rule set (i.e. combinations of conditions
  not covered)
• overlapping rules that generate inconsistency and
  redundancy
• rules that become obsolete due to new discoveries
  

26
Teiresias

• System was able to use syntactic and semantic
  knowledge from domain to assign blame to
  particular rules and make suggestions to problem
  solution
• Allows expert to focus on program errors like
  drawing false conclusions or asking irrelevant
  questions
• Program can be stopped on errors and make use of
  Mycins how/why facilities

27
Neomycin

• Uses domain independent strategy for doing
  diagnosis based on a psychological model of
  diagnostic behavior
• Uses forward chaining from known data and
  generates new hypotheses
• Maintains working memory of alternate hypotheses
  explored using a group and differentiate
  strategy

28
Rule-based Systems

• Can be used a a foundation for intelligent
  systems work since it makes use of a homogeneous
  representation of knowledge
• Allow incremental knowledge growth by adding more
  ifthen type rules
• Allow unplanned, but useful rule interactions