• Title/Summary/Keyword: Information Expert

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Analysis of Adverse Drug Reaction Reports using Text Mining (텍스트마이닝을 이용한 약물유해반응 보고자료 분석)

  • Kim, Hyon Hee;Rhew, Kiyon
    • Korean Journal of Clinical Pharmacy
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    • v.27 no.4
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    • pp.221-227
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    • 2017
  • Background: As personalized healthcare industry has attracted much attention, big data analysis of healthcare data is essential. Lots of healthcare data such as product labeling, biomedical literature and social media data are unstructured, extracting meaningful information from the unstructured text data are becoming important. In particular, text mining for adverse drug reactions (ADRs) reports is able to provide signal information to predict and detect adverse drug reactions. There has been no study on text analysis of expert opinion on Korea Adverse Event Reporting System (KAERS) databases in Korea. Methods: Expert opinion text of KAERS database provided by Korea Institute of Drug Safety & Risk Management (KIDS-KD) are analyzed. To understand the whole text, word frequency analysis are performed, and to look for important keywords from the text TF-IDF weight analysis are performed. Also, related keywords with the important keywords are presented by calculating correlation coefficient. Results: Among total 90,522 reports, 120 insulin ADR report and 858 tramadol ADR report were analyzed. The ADRs such as dizziness, headache, vomiting, dyspepsia, and shock were ranked in order in the insulin data, while the ADR symptoms such as vomiting, 어지러움, dizziness, dyspepsia and constipation were ranked in order in the tramadol data as the most frequently used keywords. Conclusion: Using text mining of the expert opinion in KIDS-KD, frequently mentioned ADRs and medications are easily recovered. Text mining in ADRs research is able to play an important role in detecting signal information and prediction of ADRs.

SWOT Analysis and Expert Assessment of the Effectiveness of the Introduction of Healthcare Information Systems in Polyclinics in Aktobe, Kazakhstan

  • Lyudmila, Yermukhanova;Zhanar, Buribayeva;Indira, Abdikadirova;Anar, Tursynbekova;Meruyert, Kurganbekova
    • Journal of Preventive Medicine and Public Health
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    • v.55 no.6
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    • pp.539-548
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    • 2022
  • Objectives: The purpose of this study was to assess the organizational effectiveness of the introduction of a healthcare information system (electronic medical records and databases) in healthcare in Kazakhstan. Methods: The authors used a combination of 2 methods: expert assessment and strengths, weaknesses, opportunities, and threats (SWOT) analysis. SWOT analysis is a necessary element of research, constituting a mandatory preliminary stage both when drawing up strategic plans and for taking corrective measures in the future. The expert survey was conducted using 2 questionnaires. Results: The study involved 40 experts drawn from specialists in primary healthcare in Aktobe: 15 representatives of administrative and managerial personnel (chief doctors and their deputies, heads of medical statistics offices, organizational and methodological offices, and internal audit services) and 25 general practitioners. Conclusions: The following functional indicators of the medical and organizational effectiveness of the introduction of information systems in polyclinics were highlighted: first, improvement of administrative control, followed in descending order by registration and movement of medical documentation, statistical reporting and process results, and the cost of employees' working time. There has been no reduction in financial costs, namely in terms of the costs of copying, delivery of information in paper form, technical equipment, and paper.

Artificial Intelligence In The Modern Educational Space: Problems And Prospects

  • Iasechko, Svitlana;Pereiaslavska, Svitlana;Smahina, Olha;Lupei, Nitsa;Mamchur, Lyudmyla;Tkachova, Oksana
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.25-32
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    • 2022
  • The hypothesis of the study of the article is that the use of elements of artificial intelligence will increase the effectiveness of the educational process of the university if: a set of pedagogical conditions for the construction and use of an expert system with elements of artificial intelligence in the educational process of the university is revealed; a model for preparing a future teacher of vocational training for the use of elements of artificial intelligence has been developed; a special course has been developed that contributes to the implementation of the professional orientation of education. In accordance with this, the following tasks were studied in the article: An analysis of scientific and methodological research in the field of the current state, prospects for the development and use of elements of artificial intelligence in the preparation of a future teacher of vocational training and to determine the dynamics of the introduction of intelligent expert systems in education; A set of pedagogical conditions for the construction and use of an expert system with elements of artificial intelligence in the educational process of a university is revealed; It is substantiated to develop a model for preparing a teacher of vocational training to use elements of artificial intelligence.

A Fundamental Study for 8 Constitution Medicine Diagnosis Expert System Development (8체질(體質) 진단(診斷) 전문가(專門家) 시스템 개발을 위한 기초연구(基礎硏究))

  • Shin, Yong-Sup;Park, Young-Bae;Park, Young-Jae;Kim, Min-Yong;Lee, Sang-Chul;Oh, Hwan-Sup
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.11 no.1
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    • pp.25-47
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    • 2007
  • Background and Purpose: There was seldom study about method that diagnose 8 Constitution beside method of pulse diagnosis in 8 Constitution Medicine. Objectives: This study is to make out check list for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning). Methods: Review of literatures about special quality element of 8 Constitution and supplement learning advice of 8 Constitution Medicine Experts constructed knowledge base. And then, knowledge base divided through AHP(Analytic Hierarchy Process), and made out check list with this. Results: Knowledge base based on special quality element of 8 Constitution was divided by 5 greate classification and 25 bisection kind, and check list consisted of 251 item was made out through this. Conclusion: Based on this research, cases necessary to make 8 Constitution Medicine Diagnosis Expert System can be gathered through check list, and further study for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning) is needed to supplement this research.

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Development of an Artificial Neural Network Expert System for Preliminary Design of Tunnel in Rock Masses (암반터널 예비설계를 위한 인공신경회로망 전문가 시스템의 개발)

  • 이철욱;문현구
    • Geotechnical Engineering
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    • v.10 no.3
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    • pp.79-96
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    • 1994
  • A tunnel design expert system entitled NESTED is developed using the artificial neural network. The expert system includes three neural network computer models designed for the stability assessment of underground openings and the estimation of correlation between the RMR and Q systems. The expert system consists of the three models and the computerized rock mass classification programs that could be driven under the same user interface. As the structure of the neural network, a multi -layer neural network which adopts an or ror back-propagation learning algorithm is used. To set up its knowledge base from the prior case histories, an engineering database which can control the incomplete and erroneous information by learning process is developed. A series of experiments comparing the results of the neural network with the actual field observations have demonstrated the inferring capabilities of the neural network to identify the possible failure modes and the support timing. The neural network expert system thus complements the incomplete geological data and provides suitable support recommendations for preliminary design of tunnels in rock masses.

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An Extended AND-OR Graph-Based Expert System in Electronic Commerce

  • 이건창;조형래;권순재
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 1999.10a
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    • pp.281-289
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    • 1999
  • The objective of this paper is to propose a brand new interface mechanism to provide more intelligent decision making support for EC problems. Its main virtue is based on a numerical process mechanism by using an Extended AND-OR Graph (EAOG)-based logic algebra. Using this mechanism, decision makers engaged in electronic commerce (EC) can effectively deal with complicated decision making problems. In the field of traditional expert systems research, AND-OR Graph approach has been suggested as a useful tool for representing the logic flowchart of the forward and/or backward chaining inference methods. However, the AND-OR Graph approach cannot be effectively used in the EC problems in which real-time problem-solving property should be highly required. In this sense, we propose the EAOG inference mechanism for EC problem-solving in which heurisric knowledge necessary for intelligent EC problem-solving can be represented in a form of matrix. Finally, we have proved the validity of our approach with several propositions and an illustrative EC example

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Implementation of a Rule Generation Module for Expert System using RIPPER (PIPPER를 이용한 전문가시스템의 규칙 생성 모듈 구현)

  • 김군오;김진상
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 1999.10a
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    • pp.131-137
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    • 1999
  • 전문가시스템 개발에 있어서 지식획득 병목현상(knowledge acquisition bottleneck)은 해결해야 할 큰 걸림돌중 하나이다. 지식획득을 위한 여러 과정을 단순화하고 자동화함으로 지식공학자의 작업을 최소화하면서 전문지식을 쉽고 빠르게 획득할 수 있도록 지식획득시스템을 설계·구현한다면 전문가시스템의 대중화는 지금보다 쉽게 이루어질 것이다. 본 연구는 지식 획득시스템 설계와 구현을 위한 연구의 일환으로 기계학습의 한 방법인 PIPPER(Repeated Incremental Pruning to Produce Error Reduction)를 이용하여 규칙을 생성하고 생성된 규칙을 JESS(Justification based Expert System Shell)에서 처리하도록 하였다. 규칙을 생성하기 위한 데이터는 Bohanec이 1997년도에 만든 자동차 평가 데이터베이스(Car Evaluation Database)를 사용하여 실험하였으며, 1700여 개의 레코드에서 약 40개의 규칙이 생성되었고, 생성된 규칙은 지식베이스의 정당성을 위반하지 않으면서 실행되었다.

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An Artificial Neural Network Model Approach to Predict Managers and Business Students Motivational Levels Using Expert Systems

  • 이용진;윤종훈
    • The Journal of Information Systems
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    • v.5
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    • pp.205-248
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    • 1996
  • Historically, the en-users' acceptance of the expert systems(ES) have generally been used as a proxy for the ES' implementation success by both practitioners and academicians. However, with regard to bank loan decisions, most loan officers approach the acquisition of an ES with apprehension. In order to overcome this skepticism, more research should focus on the behavioral aspects relate to systems acquisition and usage. This research applied Vroom's(1964) expectancy theory in an effort to predict end-users' motivation to use an ES in a bank loan decision context. Because human behaviors and judgements are nonlinear rather than linear functions, accurately predicting human behavior is very difficult. To increase the prediction power for end-users' motivation to use an ES in a bank loan decision context, this research used an artificial neural network (ANN) model. In this research, an attempt was made to evaluate adequacy of the surrogates by analyzing differences between real bank loan officers and student surrogates in applying expectancy theory to estimate bank loan officers' motivation to use ES in a bank loan decision context.

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A Fault Diagnosis System of Glass Melting Furnace Using A Fuzzy Expert System (퍼지 전문가 시스템을 이용한 유리 용해로 이상 감시 시스템 구축 사례)

    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.65-65
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    • 2002
  • 본 논문에서는 용해로 이상감시를 위한 실시간 유리 용해로 운전 전문가시스템을 구축한 결과를 소개한다. 유리 용해 공정에서는 운전자의 경험지식에 의해 내부의 상황을 판단하게 되고, 이는 용해로 수명과 제품의 품질에 중요한 영향을 준다. 이를 전문가 시스템으로 구현하기 위하여, 먼저 기존 운전자의 지식을 취합, 분석한다. 그 후,취합된 각 지식들의 특성에 부합하도록 이진 규칙(Crisp Rule)과 퍼지 규칙(Fuzzy Rule)으로 구분한다. 이 때, 선형 회귀분석을 통하여 퍼지 규칙의 입력을 결정함으로써 보다 정확한 운전 지식의 표현이 가능하도록 하였다. 설계된 알고리듬은 젠심(Gensym)사의 실시간 전문가 시스템 개발 툴인 G2를 사용하여 구현하였다. 제시된 퍼지 전문가 시스템은 삼성코닝(주) 수원사업장의 실제 생산 용해 공정에 직접 적용하여 그 효율성이 검증되었다.

Remote Diagnosis of Hypertension through HTML-based Backward Inference

  • Song, Yong-Uk;Chae, Young-Moon;Cho, Kyoung-Won;Ho, Seung-Hee
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.496-507
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    • 2001
  • An expert system for the diagnosis and indication of hypertension is implemented through HTML-based backward inference. HTML-based backward inference is performed using the hypertext function of HTML, and many HTML files, which are hyperlinked to each other based on the backward rules, should be prepared beforehand. The development and maintenance of the HTML files are conducted automatically using the decision graph. Still, the drawing and input of the decision graph is a time consuming and tedious job if it is done manually. So, automatic generator of the decision graph for the diagnosis and indication of hypertension was implemented. The HTML-based backward inference ensures accessibility, multimedia facilities, fast response, stability, easiness, and platform independency of the expert system. So, this research reveals that HTML-based inference approach can be used for many Web-based intelligent site with fast and stable performance.

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