Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Abstraction in Belief Networks: The Role of Intermediate States in
  Diagnostic Reasoning   Bayesian belief networks are bing increasingly used as a knowledge
representation for diagnostic reasoning. One simple method for conducting
diagnostic reasoning is to represent system faults and observations only. In
this paper, we investigate how having intermediate nodes-nodes other than fault
and observation nodes affects the diagnostic performance of a Bayesian belief
network. We conducted a series of experiments on a set of real belief networks
for medical diagnosis in liver and bile disease. We compared the effects on
diagnostic performance of a two-level network consisting just of disease and
finding nodes with that of a network which models intermediate
pathophysiological disease states as well. We provide some theoretical evidence
for differences observed between the abstracted two-level network and the full
network.

32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph