• Genomics & Informatics
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• 제11권4호
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• pp.186-190
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• 2013

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

• 스마트미디어저널
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• 제5권1호
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• pp.114-121
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• 2016

현재 각 의료기관들은 의료정보화 사업을 꾸준히 진행 하고 있다. 의료기관에서 운영하고 있는 대표적인 시스템으로는 전자의무기록, 처방전달시스템 등이 있으며, 의료법에서 전자서명을 허용함으로써 의료정보를 관리함에 있어 비용절감 및 진료정보의 공유가 가능하게 되었고, 공인인증서를 활용한 의료솔루션 사용이 확산되어 가고 있다. 이러한 현실에서 인증서의 역할은 어느 무엇보다 중요하다고 할 수 있지만, 대부분 개인 인증서 관리에는 매우 적극적인 반면, 의료솔루션 등 업무와 관련된 인증서 관리에 대해서는 소홀한 것이 사실일 것이다. 업무용 인증서의 경우 업무PC에 보관하는 경우가 다수이며 이는 보안에 취약할 수밖에 없다. 이에 대한 해결책으로 인증서 서버가 존재하나 별도서버의 구축이 필요하여 중소병원의 경우 비용에 대한 부담이 적지 않을 것으로 판단된다. 본 논문에서는 추가비용을 최소화하여 별도의 인증서 서버를 구축하지 않고 인증서 파일을 BLOB로 저장하여 현재의 자원을 활용한 인증서 관리 및 보안에 효과적인 시스템을 설계 및 구현 하고자 한다.

• Journal of Information Processing Systems
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• 제12권2호
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• pp.263-274
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• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

• Journal of Preventive Medicine and Public Health
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• 제39권5호
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• pp.433-437
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• 2006

Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

• 정보처리학회논문지D
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• 제9D권5호
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• pp.769-778
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• 2002

LEX(Lifelong EHR based on XML)시스템은 이질적인 병원정보시스템을 가진 병원들이 HL7 메시지를 생성하고, 이를 통해 의료정보를 효율적으로 공유하고 교환할 수 있는 중앙의 임상데이터베이스(Central Clinical DataBase/CCDB)를 구축하는 XML 기반의 의료정보통합 프래임 워크이다. 본 논문에서는 기존의 병원정보시스템에 독립적인 HL7 메시지 서버 연동방식을 제안하여 HL7 메시지를 생성하고, 생성된 메시지를 효율적으로 저장하고 검색하기 위한 환자중심의 XML데이터베이스 스키마를 제안한다. 또한 HL7 메시지를 새로운 구조의 XML문서로 변환하기 위한 DTD를 제안함으로써 기존의 방식보다 저장공간을 절약하고, 효율적인 환자중심의 검색을 지원하는 방안을 제시한다.

• Journal of Chest Surgery
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• 제25권10호
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• pp.989-1000
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• 1992

The concepts of modern type computer are so called "General purpose, stored program and digital computer" that is proposed by Charles Babbage. ENIAC, the initial operational electronic digital computer model, was produced in 1946. During the last 50 years, an epoch-making development of the personal computer was marked. The computerization of all levels of society is going on and also computerization of the general hospital and medical college is developing. But patient data management system for clinician is not used generally. We suggest the use of computer aided data management application programs for the clinical informations of the patients of the Department of Thoracic and Cardiovascular Surgery for better management and to make best of medical informations, to co-operate with the current of this times, and to prepare against the Hospital Information Systems[HIS], actively. Also, we suggest to standardize the format and structure of database files to store the clinical data of the patients By standardization of the database files, we can integrate and relate the data of the individual department or hospital, build up the regional or national statistics of the patients easily, and promote the generation of application programs. The medical network by the communication and computer would be utilized to collect the database files. And finally, we suggest the use of code system to input and search the informations about the diagnosis and operation such as the code system of International Classfication of Disease[WHO] and the table of the classfication of operation of the Ministry of Health and Social Affairs, Korea. In this article, we tried to show the new standards, the essential items for computerization of clinical informations of the patients of the Department of Thoracic and Cardiovascular Surgery.r Surgery.

• 한국산학기술학회논문지
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• 제8권6호
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• pp.1496-1504
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• 2007

본 논문은 헬스케어 연구의 일환으로 병원 내의 EMR(Electronic Medical Record)을 지원할 수 있는 환자 자동인식 시스템의 설계 및 구현이다. 기존의 종이형 차트를 대신할 수 있으면서, 빠르고 정확한 환자 인식이 가능하고, 기존 EMR의 데이터베이스를 사용할 수 있는 모바일 기기 기반의 시스템을 개발하였다. 환자의 인식에는 RFID(Radio Frequency IDentified)를 사용하였으며, RFID와 시스템의 연동을 통해 자동화 된 환자 인식이 가능하다. 개발된 시스템은 테스트 베드에서 테스트하여 기존 종이형 차트에 비해 빠른 진료가 가능함을 실험하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.268-275
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• 2014

In future, hospitals are expected to automatically issue remote transcriptions. Many general hospitals are planning to encrypt their medical database to secure personal information as mandated by law. The electronic medical record system, picture archiving communication system, and the clinical data warehouse, amongst others, are the preferred targets for which stronger security is planned. In the near future, medical systems can be assumed to be automated and connected to remote locations, such as rural areas, and islands. Connecting patients who are in remote locations to medical complexes that are usually based in larger cities requires not only automatic processing, but also a certain amount of security in terms of medical data that is of a sensitive and critical nature. Unauthorized access to patients' transcription data could result in the data being modified, with possible lethal results. Hence, personal and sensitive data on telemedicine and medical information systems should be encrypted to protect patients from these risks. Login passwords, personal identification information, and biological information should similarly be protected in a systematic way. This paper proposes the use of electronic acupuncture with a built-in multi-pad, which has the advantage of being able to establish a patient's physical condition, while simultaneously treating the patient with acupuncture. This system implements a sensing pad, amplifier, a small signal drive circuit, and a digital signal processing system, while the use of a built-in fuzzy technique and a control algorithm have been proposed for performing analyses.

• 대한원격탐사학회지
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• 제22권5호
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Journal of International Society for Simulation Surgery
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• 제4권1호
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• pp.21-23
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• 2017

Purpose In this paper, we proposed alternate neighborhood system and reverse spread-direction approach for accurate and fast cellular automata-based image segmentation method. Materials and Methods On the basis of a simple but effective interactive image segmentation technique based on a cellular automaton, we propose an efficient algorithm by using Moore and designed neighborhood system alternately and reversing the direction of the reference pixels for spreading out to the surrounding pixels. Results In our experiments, the GrabCut database were used for evaluation. According to our experimental results, the proposed method allows cellular automata-based image segmentation method to faster while maintaining the segmentation quality. Conclusion Our results proved that proposed method improved accuracy and reduced computation time, and also could be applied to a large range of applications.