User's Comment Classifying Method Using Self Organizing Feature Map on Healthcare System for Diabetic

URI http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/2971
File
Title
User's Comment Classifying Method Using Self Organizing Feature Map on Healthcare System for Diabetic
Author
氏名 MERA Kazuya
ヨミ メラ カズヤ
別名 目良 和也
氏名 ICHIMURA Takumi
ヨミ イチムラ タクミ
別名 市村 匠
Abstract

Diabetes is a metabolic disorder characterized by the elevation of blood glucose. Glysemic control can delay the onset and slow progression of vascular complications. Lifestyle modification including weight reduction can contribute significantly to glysemic control. The Health Support Intelligent System for Diabetic Patients(HSISD) can provide guideline-based decision support for life style modifications in the treatment of diabetes. HSISD also provides opportunities for telecounseling(TC) with the use of mobile devices and the Internet. The telecounseling phase inquires about the patient's condition and the patient answer in a questionnaire. In the questionnaire, there is a question like "Have you developed any symptoms of anxiety? If yes, tell me the details." The answer is described freely so the physician should read all of patient's answer. But it is hard for physicians to read all text carefully because a physician has a lot of patients. We propose a method to analyze text data from the patients and classify them into five anxiety types(mental problem, physical problem, diet, physical activity, and medicine) automatically. Related to the classified anxiety type, the method can analyze the patient's inner emotion to guess serious and emergency degree of the patient. In this method, Self organizing feature map is trained by the distribution of feature words(morphemes) in the input text and also classifies anxiety type and emotion type.

Description Peer Reviewed
Journal Title
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
Spage
31
Epage
36
Published Date
2008-12
Publisher
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
Language
eng
NIIType
Conference Paper
Text Version
出版社版
Rights
©Copyright by IEEE SMC Hiroshima Chapter. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
Old URI
Set
hiroshima-cu