• 대한전자공학회논문지
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• 제23권5호
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• pp.658-665
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• 1986

In this paper, we study a (condition interprete systdem CCIS) which is a general purpose inference system for building an expert system. Previously, most expert systems used fragmentary knowledge-representation and inexact inferencing methods. To solve the proboems of those systems we suggest an algorithm for more flexible deduction and a method of representing knowledge more naturally and consistently compared to those of other experst systems. The CIS is a systsdem which can infer all the current situations from communication with the user based on user discription of some situation. we used some medical data on hypertension and its complication to simulate the system and to prove the effectiveness of the system. The results show that with the proposed method one can realize an attractive expert system.

• Journal of applied mathematics & informatics
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• 제38권5_6호
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• pp.533-545
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• 2020

We initiate and introduce the notion of binary soft mapping, which is defined on collection of binary soft sets named as binary soft class over two initial universes U₁ and U₂ with fixed set of parameters. We also define and study the properties of binary soft images and binary soft inverse images of binary soft sets. Examples and counter examples are also given in support of presented properties. Moreover, these concepts are applied to the problem of medical diagnosis in medical expert systems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.111-114
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• 2004

Management of human knowledge is an interesting concept that has attracted the attention of philosophers for thousands of years. Artificial intelligence and knowledge engineering has provided some degree of rigor to the study of knowledge systems and expert systems(ES) re able to use knowledge to solve the problems and answer questions. Therefore, the process of conceptualization and inference of knowledge are fundamental problem solving activities and hence, are essential activities for solving the problem of software ES construction Especially, the access to relevant, up-to-date and reliable knowledge is very important task in the daily work of physicians and nurses. In this study, we propose the conceptualization and inference mechanism for implicit knowledge management in medical diagnosis area. To this purpose, we combined the dynamic knowledge map(KM) and relational database(RDB) into a dynamic knowledge map(DKM). A graphical user-interface of DKM allows the conceptualization of the implicit knowledge of medical experts. After the conceptualization of implicit knowledge, we developed an RDB-based inference mechanism and prototype software ES to access and retrieve the implicit knowledge stored in RDB. Our proposed system allows the fast comfortable access to relevant knowledge fitting to the demands of the current task.

• 한국지능시스템학회논문지
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• 제1권1호
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.288-291
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• 2003

For the purpose of building the more efficient knowledge learning system, it is very important to make a good structure of the knowledge system first of all. The well designed knowledge system can make the stored knowledge to be easily accessed for knowledge acquisition and extraction. Expert knowledge can also play a good role for controlling. Accordingly, in this paper we propose the Hierarchical modular system with expert knowledge gating mechanism. This system consists of the mechanisms for knowledge acquisition, constructing the associative memory, knowledge inference and extraction according to the expert knowledge gating mechanism. We applied this system to the medical diagnostic area for classifying Virus(coxackie virus, echovirus, cold), Rhinitis(Nonallergic, allergic) and tested with symptom data

• 한국정보통신학회논문지
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• 제8권4호
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• pp.873-878
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• 2004

본 연구에서는 뇌졸중 초기증상의 분석으로 뇌졸중 진단을 웹상에서 간단하고 편리하게 제공하고 일반인들의 뇌졸중에 대한 지식향상으로 뇌졸중을 사전에 예방할 수 있는 뇌졸중 진단 전문가 시스템 서버를 개발하였다. 또한 신경학을 전공하는 의대생들에게도 새로운 학습용 진단 시뮬레이터를 제공하도록 하였다. 전문가 시스템의 구현 방법은 여러 가지가 있으나 본 연구에서는 인공 신경회로망과, ASP(active server page)라는 웹 프로그래밍을 이용하여 뇌졸중 진단 전문가 시스템의 추론 엔진과 서버를 설계하였다.

• Journal of Preventive Medicine and Public Health
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• 제55권6호
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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.

• 대한핵의학회지
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• 제33권3호
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• pp.282-288
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• 1999

목적: 골밀도는 DXA 기종에 따라 그 측정치의 차이가 발생하는 것으로 알려져 있어 현재 널리 사용중인 Lunar EXPERT-XL과 Hologic QDR 4500-A에서 측정된 골밀도의 차이를 비교하고 그 차이를 보정할 수 있는 교차보정식을 구하고자 하였다. 대상 및 방법: 109명의 여성(평균 나이; $55{\pm}11$년)을 대상으로, 같은 날 대상 환자의 제2-4 요추와 대퇴골 경부를 Lunar EXPERT-XL과 Hologic QDR 4500-A로 각각 촬영하여 얻어진 측정 영역(area)과 골무기질양(BMC), 골밀도(BMD)와 정상 골밀도 참고치에 대한 백분율의 차이를 분석하였다. 또한 측정영역, 골무기질양, 골밀도와 정상 골밀도 참고치에 대한 백분율에 대해 각각 선형 회귀 분석으로 교차 보정식(cross-calibration equation)과 상관 계수(R), 표준 예측 오차(SEE)를 구하였다. 결과: Lunar 기종으로 측정한 제2-4 요추와 대퇴골경부의 골밀도(각각 평균 $0.955{\pm}0.17g/cm^2$, $0.767{\pm}0.131g/cm^2$)가 Hologic 기종으로 측정한 값보다(각각 $0.851{\pm}0.144g/cm^2$, $0.649{\pm}0.108g/cm^2$) 각각 평균 13%와 19% 높았다. 골무기질양과 정상 골밀도 참고치에 대한 백분율도 Lunar 기종에서 모두 유의하게 높았으나(p<0.001), 측정영역은 두 기종간의 차이가 없었다(p>0.05), 두 기종간 골밀도는 높은 상관관계(r>0.95)를 보였고 교차 보정식은 제2-4 요추에서 Lunar=1.1297${\times}$Hologic-0.0027, 대퇴골 경부에서 Lunar=1.1556${\times}$Hologic+0.0182 이었다. 결론 두 DXA 기종간의 골밀도 측정치는 서로 차이가 있었으나 높은 상관 관계를 보여 교차 보정식을 얻을 수 있었다. 이 교차 보정식은 환자의 추적 검사상 불가피하게 다른 기종으로 검사를 받은 경우나 하나의 기종으로 검사를 받은 연구 집단의 결과를 다른 기종으로 검사한 연구 집단의 결과와 비교 분석시 유용하리라 생각한다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권3호
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• pp.92-103
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• 2021

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2003년도 춘계학술대회
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• pp.271-285
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• 2003

In the conduct of this study, a web-enabled healthcare system for the management of hypertension was implemented through a hyperlink-based inference approach. The hyperlink-based inference platform implemented using the hypertext capacity of HTML which ensured accessibility, multimedia facilities, fast response, stability, ease of use and upgrade, and platform independency of expert systems. Many HTML documents, which are hyperlinked to each other based on expert rules, were uploaded beforehand to perform the hyperlink-based inference. The HTML documents were uploaded and maintained automatically by our proprietary tool called the Web-Based inference System (WeBIS) that supports a graphical user interface (GUI) for the input and edit of decision graphs. Nevertheless, the editing task of the decision graph using the GUI tool is a time consuming and tedious chore when the knowledge engineer must perform it manually. Accordingly, this research implemented an automatic generator of the decision graph for the management of hypertension. As a result, this research suggests a methodology for the development of Web-enabled healthcare systems using the hyperlink-based inference approach and, as an example, implements a Web-enabled healthcare system for hypertension, a platform which peformed especially well in the areas of speed and stability.