PROCEEDINGS IPMU '08
Graphical exploratory analysis of vague data in the early diagnosis of dyslexia
Luciano Sánchez, Ana Palacios, M. R. Suárez, Inés Couso
We are in the initial stages of the
design of a fuzzy rule-based testing
system that can be used by unqualified
personnel while screening
the children for dyslexia. The main
novelty of our work is the exploitation
of low quality data (incomplete
items, intervals, lists, subjective values,
etc.) A sample of infants has
been obtained, and some tests have
been applied to them. In addition,
a psychologist has examined and diagnosed
each child. We want to relate
the responses to the tests with
the expert judgement of the professional,
and highlight those factors
that are involved in the early development
of the dyslexia during the
preschool age. However, this data
being imprecise, we lack tools to assess
the quality of each test and its
influence in the diagnosis. We have
used different graphical visualization
techniques, to detect the most useful
sets of factors, but have found
that none of the approaches that we
are aware of is able to show all the
relevant information in the sample.
Therefore, we propose a new Multidimensional
Scaling algorithm, that
gains a better insight into the spatial
properties of the data and also
into the amount of vagueness in the
pieces of information comprising it.
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