### Abstract

Medical databases appear in general as collections of scarcely
defined, uncomfortable feelings, disturbances and disabilities of
patients encoded in medical terms and symptoms, often scarcely
enriched with some ordinal and metric data. But, astonishing
enough, in many cases this is sufficient for an experienced
practitioner to attend successfully. First necessity for a
scientific evaluation of such sort of database is to get as much
specific information as available from as many patients as
possible. This is essential because of the great variability of
human diseases. The next step is to extract relevant data from the
database addressed to the question of interest and the anticipated
answers and models, which assign relevance to data. The data has
to be objective, reliable, constant, and independent. The
independence is the main topic of this paper. Several methods like
analysis of variance, analysis of discriminance, multiple
regression and factor analysis offer the possibility to control
the interdependence of data.Factor analysis has the advantage that
it is based on a mathematical model, and does not ask for normal
distribution of the data. Factor analysis describes the
correlation of many variables by few independent factors. The
number of factors which can be extracted from a correlation matrix
is a reliable criterion for inherent independent information in
that matrix. Several data sets were analyzed, which were gained
from the Aphasia Database, such as different groups of patients,
groups of symptoms, and symptoms in time sequence.26 aphasic
symptoms (e.g. dysarthria, paraphasias, neologisms, agrammatism,
etc.) documented in reports of the 265 aphasic patients provide 3
factors. If the symptoms were graded according to the severity of
disability in the individual cases, then 5 factors were extracted.
The factors had different relationships (loadings) to the
symptoms. Although the factors were gained only by computations,
they seemed to express some modular features of the language
disturbances. This phenomenon, that factors represent superior
aspects of data, is well known in factor analysis. Factor I
mediates the overall severity of the disturbance, factor II points
to expressive versus comprehensive character of the language
disorder, factor III represents the granularity of the phonetic
mistakes, factor IV accentuates the patients' awareness of his
disease, and factor V exposes the deficits in communication. Sets
of symptoms corresponding to the traditional symptoms in Broca and
Wernicke aphasia may be represented in the factors, but the factor
itself does not represent a syndrome. It is assumed that this kind
of data analysis shows a new approach to the understanding of
language disturbances, which should represent functional entities
of the brain more closely than the traditional clinical
descriptions do.

Original language | English |
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Title of host publication | ESIT 2000 Final Programme and Proceedings (Abstracts and CD) |

Publication date | 2000 |

Publication status | Published - 2000 |

Event | European Symposium on Intelligent Techniques - Aachen, Germany Duration: 14 Sep 2000 → 15 Sep 2000 |

### Conference

Conference | European Symposium on Intelligent Techniques |
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Country | Germany |

City | Aachen |

Period | 14/09/2000 → 15/09/2000 |

## Cite this

Keyserlingk, D. G. V., Jantzen, J., Berks, G., Keyserlingk, A. G. V., & Axer, H. (2000). Critical Data Analysis Precedes Soft Computing Of Medical Data. In

*ESIT 2000 Final Programme and Proceedings (Abstracts and CD)*