Advanced Information Technology - Support of Improved Personalized Therapy of Speech Disorders

Authors

  • Mirela Danubianu “Ştefan cel Mare” University of Suceava Romania, 720229 Suceava, 13 Universităţii
  • Stefan Gheorghe Pentiuc “Ştefan cel Mare” University of Suceava Romania, 720229 Suceava, 13 Universităţii
  • Ovidiu Andrei Schipor “Ştefan cel Mare” University of Suceava Romania, 720229 Suceava, 13 Universităţii
  • Iolanda Tobolcea “Alexandru Ioan Cuza” University of IaÅŸi Romania, 700506 Iasi, 11 Bulevardul Carol I

Keywords:

personalized therapy, data mining, classification, clustering, associations rules

Abstract

One of the key challenges of the Sustainable Development Strategy adopted by the European Council in 2006 is related to public health whose general objective envisages a good level of public health. One of the specific targets includes better treatments of diseases. It is true that there are affections which by their nature do not endanger the life of a person, however they may have a negative impact on her/his life standard. Various language or speech disorders are part of this category, but if they are discovered and treated in due time, they can be often corrected. The difficulty for researchers and therapists is to identify those children who have disorders that show a wide range of issues that cannot be solved spontaneously or which may lead to further significant deficiencies. Information technology in the latest years was used by specialists in order to assist and supervise speech disorder therapy. Consequently they have collected a considerable volume of data about the personal or familial anamnesis, regarding various disorders or regarding the process of personalized therapies. These data can be used in data mining processes that aim to discover interesting patterns which can help the design and adaptation of different therapies in order to obtain the best results in conditions of maximum efficiency. The aim of this paper is to present the Logo-DM system. This is a data mining system that can be associated with TERAPERS system in order to use the data from its database as a source for analysis and to provide new information based on an improved system of therapy. Through the use of appropriate techniques of data mining Logo-DM realizes predictions on the evolution and the final status of patients undergoing therapy and enriches the knowledge data of expert system embedded in TERAPERS.

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Published

2010-12-01

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