Information Technology Reference
In-Depth Information
The one that follows is an example of a rule of this type:
IF positive rheumatoid factor
THEN NOT seronegative rheumatoid arthritis
Type always occurring ( ao ). A rule of type ao is of the form
θ , φ
medical entities. It can be triggered by the system only when there is certainty
about the falsity or non-occurrence of
θ , φ ,
1
,for
φ
.
A rule of type ao expresses the fact that the antecedent implies the consequent. It
follows that, if the consequent is excluded, the presence of the antecedent is also
excluded.
Notice that a rule
θ , φ ,
1
of type ao can be alternatively formalized by the triple
φ ,∼ θ ,
1
and that it is not a special case of a rule of type c due to the fact that
θ
is not a basic medical entity.
Next we give an example of a rule of this type:
IF NOT ( rheumatoid arthritis AND splenomegaly AND leukopenia
4000
l )
THEN NOT Felty's syndrome
/ μ
There are other typologies for the rules in KR that will prove useful in further sec-
tions in this paper. A very general typology is the one that follows:
Binary rules. Rules of the form
θ , φ , η
where
θ , φ
are basic entities.
Compound rules. Rules of the form
θ , φ , η
where
θ
is a compound medical
entity and
φ
is a basic entity.
The vast majority of rules in KR are binary. There are less than one hundred com-
pound rules in KR yet, despite the number, they are important for the functioning of
the system.
We have a further distinction among binary rules of use in further sections:
Symptom-symptom rules. Rules of the form
θ , φ , η
where both
θ , φ
are symp-
toms and
η ∈{
0
,
1
}
.
Diagnose-diagnose rules. Rules of the form
θ , φ , η
where both
θ , φ
are diag-
noses and
η ∈{
0
,
1
}
.
Symptom-diagnose rules. Rules of the form
θ , φ , η
where
θ
is a symptom,
φ
a diagnose and
η [
0
,
1
]
.
Diagnose-symptom rules. Rules of the form
θ , φ , η
where
θ
is a diagnose,
φ
is a symptom and
η [
0
,
1
]
.
Most rules of type diagnose-symptom in KR are not used by the inference engine,
only those of type ao areusedbyit.
The Inference Engine. CADIAG2 gets started with medical information about
the patient. Such information is formally given by a set of basic medical entities
present in the patient, each one together with a number in the interval
which,
in principle, is intended to represent the degree to which such entity is present
[
0
,
1
]
Search WWH ::




Custom Search