• Title/Summary/Keyword: 지능적 의학 전문가 시스템

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지식공학을 위한 하드웨어

  • 황시영
    • The Magazine of the IEIE
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    • v.15 no.3
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    • pp.43-50
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    • 1988
  • 대다수의 사람들이 갖고 있지 않은 특정분야-예를 들어 의학, 법률, 과학적 분석, 회로설계 등-의지식을 요하는 일은 이에 필요한 지식을 갖춘 전문가에 의해서만 가능하였으나 최근 컴퓨터 기술의 발달로 이런 일을 해주는 프로그램의 탄생을 보게 되었으며 이런 프로그램을 전문가 시스템이라고 하고 전문가 시스템을 구축하는 일을 지식공학(knowledge engineering)이라고 한다. 지식공학은 인공지능을 응용면에서 추구하는 바이며 지적기능을 프로그램화하는 과학이라 할 수 있다. 먼저 지식공학을 위한 컴퓨터 구조를 기술하기 전에 인공지능 응용 프로그램의 특징에 대해 언급하고자 한다.

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Design and Implementation of an Intelligent Medical Expert System for TMA(Tissue Mineral Analysis) (TMA 분석을 위한 지능적 의학 전문가 시스템의 설계 및 구현)

  • 조영임;한근식
    • Journal of KIISE:Software and Applications
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    • v.31 no.2
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    • pp.137-152
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    • 2004
  • Assesment of 30 nutritional minerals and 8 toxic elements in hair are very important not only for determining adequacy, deficiencies and unbalance, but also for assessing their relative relationships in the body. A test has been developed that serves this purpose exceedingly well. This test is known as tissue mineral analysis(TMA). TMA is very popular method in hair mineral analysis for health care professionals in over 46 countries' medical center. However, there are some problems. First, they do not have database which is suitable for korean to do analyze. Second, as the TMA results from TEI-USA is composed of english documents and graphic files prohibited to open, its usability is very low. Third, some of them has low level database which is related to TMA, so hairs are sent to TEI-USA for analyzing and medical services. it bring about an severe outflow of dollars. Finally, TMA results are based on the database of american health and mineral standards, it is possibly mislead korean mineral standards. The purposes of this research is to develope the first Intelligent Medical Expert System(IMES) of TMA, in Korea, which makes clear the problems mentioned earlier IMES can analyze the tissue mineral data with multiple stage decision tree classifier. It is also constructed with multiple fuzzy rule base and hence analyze the complex data from Korean database by fuzzy inference methods. Pilot test of this systems are increased of business efficiency and business satisfaction 86% and 92% respectively.

A Study on the U-Healthcare Diagnosis System for Mobile Environment (모바일 환경에서의 U-Healthcare 진단 시스템에 관한 연구)

  • Kim, Heon
    • Journal of Digital Contents Society
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    • v.7 no.4
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    • pp.245-249
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    • 2006
  • In the rapidly changing high-tech society, lots of people are exposed to various kinds of stress and disease with an effort to adopt to the society, in spite of the benefits and abundance created by various technologies. Therefore, the health of modem people is our main concern and essential subject. The researcher would like to suggest systematical and intelligent medical diagnosis expert system that can give the effect same as the help from real experts with health check helper and scientific and objective knowledge that fit to the age and environment of changing.

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Design and Embodiment for Constructing Mobile Medical Information System Combining Bio-sensor and IT Technology (바이오센서 기술과 IT기술을 융합한 휴대용 의료정보 시스템 구축을 위한 설계 및 구현)

  • Kim, Heon;Lee, Sung-Koo
    • Journal of Digital Contents Society
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    • v.9 no.1
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    • pp.27-31
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    • 2008
  • u-Health is a representative realization method of ubiquitous IT and it is being embossed as an industry that can make our lives abundant. Through the u-Health, the diagnosis will go beyond the restriction of space, which is based on hospital, and be positioned as a universal value in a daily life by combining diagnosis and life naturally. The purpose of this study is to suggest systematic, intelligent, mobile medical information system that has the same effect as the assistant of specialist by providing scientific and objective knowledge, which is suitable for u-Health age. Mobile medical information system can provide user with the opinion of specialist by planting the experience, knowledge and decision making process of specialist that are necessary for solving the problem requiring special medical knowledge and passing through an inference process.

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A Study on Usability Evaluation for Human Care Contents based Rehabilitation Training Equipment (휴먼 케어 콘텐츠 기반의 재활 훈련 장비의 사용성 평가 연구)

  • Kim, Hansang;Choi, Byung-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.27 no.2
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    • pp.157-163
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    • 2017
  • Due to economic development and advancement of medical science, an aging society where the proportion of the elderly population increases is coming. Korea's aging speed is growing rapidly compared to that of other developed countries. The physical and mental abilities of elderly people with aging are getting worse more and more. They want a kind of auxiliary system in order to mitigate and prevent their weakness. The supplementary system can greatly contribute to improving the quality of life for elderly people. In particular, some devices that include muscle strengthening and cognitive and balance ability enhancement are useful for the most older people. In this paper, we introduce a development of human care contents based rehabilitation equipment to enhance these functions, and present its usability evaluation. The evaluation is conducted for rehabilitation specialists as well as expected users and their results are analyzed.

Fully Automatic Heart Segmentation Model Analysis Using Residual Multi-Dilated Recurrent Convolutional U-Net (Residual Multi-Dilated Recurrent Convolutional U-Net을 이용한 전자동 심장 분할 모델 분석)

  • Lim, Sang Heon;Lee, Myung Suk
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.2
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    • pp.37-44
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    • 2020
  • In this paper, we proposed that a fully automatic multi-class whole heart segmentation algorithm using deep learning. The proposed method is based on U-Net architecture which consist of recurrent convolutional block, residual multi-dilated convolutional block. The evaluation was accomplished by comparing automated analysis results of the test dataset to the manual assessment. We obtained the average DSC of 96.88%, precision of 95.60%, and recall of 97.00% with CT images. We were able to observe and analyze after visualizing segmented images using three-dimensional volume rendering method. Our experiment results show that proposed method effectively performed to segment in various heart structures. We expected that our method can help doctors and radiologist to make image reading and clinical decision.