Using a Knowledge-based System for Validating and Classifying Requests in Large-scale Laboratories, Considering Preliminary Diagnoses.
K. Breuer - Using a Knowledge-based System for Validating and Classifying Requests in Large-scale Laboratories, Considering Preliminary Diagnoses. - Proceedings of FH Science Day 2005, Steyr, Austria, 2005, pp. 7
Motivation: In general, an expert system for improving quality assurance for incoming requests
in large-scale laboratories is designed and implemented, which works to a large extend independent from human individuals as it uses past
request data supplied by the laboratories.
In particular, this expert system (LabExpert) is
extended to incorporate not only information on
valid test compositions for requests, but also information on preliminary diagnoses using NLP
(natural language processing) methods to enable
the underlying knowledge-base to perform a more precise quality assessment.
Results: The incorporation of preliminary diagnoses
to LabExpert only provides significant results
within a given gray area, as the number of requests containing an utilizable preliminary diagnosis within the training data account for only 6.7%.
Within this area, LabExpert shows clearly the
benefit of using NLP methods to provide further
parameters for classification and adaptation.
Availability: LabExpert is not available due to
special nondisclosure agreements with cooperation