DocumentCode
1687570
Title
Towards the Optimized Personalized Therapy of Speech Disorders by Data Mining Techniques
Author
Danubianu, Mirela ; Pentiuc, Stefan Gheorghe ; Socaciu, Tiberiu
Author_Institution
Fac. of Electr. Eng. & Comput. Sci., Stefan cel Mare Univ. of Suceava, Suceava, Romania
fYear
2009
Firstpage
20
Lastpage
25
Abstract
Various speech disorders or language impairments can affect the whole life of a person. Discovered and treated in time, they can be corrected, most often in childhood. The use of information technology in order to assist and supervise speech disorder therapy allows specialists to collect a considerable volume of data about the personal or familial anamnesis, regarding various disorders or regarding the process of personalized therapy. These data can be the foundation of data mining processes that show interesting information for 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 make a short analyze of the use opportunity of the data mining techniques in order to improve the personalized therapy of speech disorders framework. We also present Logo-DM, a data mining system designed to be associated with TERAPERS system in order to provide information based on which one could improve the process of personalized therapy.
Keywords
data mining; medical computing; medical disorders; patient treatment; speech; Logo-DM; TERAPERS system; data mining techniques; familial anamnesis; information technology; language impairments; optimized personalized therapy; personal anamnesis; speech disorder therapy; Data mining; Information technology; Medical services; Medical treatment; Natural languages; Pediatrics; Speech analysis; Speech processing; Speech recognition; Speech synthesis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing in the Global Information Technology, 2009. ICCGI '09. Fourth International Multi-Conference on
Conference_Location
Cannes, La Bocca
Print_ISBN
978-1-4244-4680-3
Electronic_ISBN
978-0-7695-3751-1
Type
conf
DOI
10.1109/ICCGI.2009.11
Filename
5279770
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