• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1172-1181
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• 2009

An electronic medical record (EMR) is the medical system that all the test are recorded as text data. However, domestic EMR systems have various forms of medical records. There are a lot of related works to standardize the laboratory codes as a LOINC (Logical Observation Identifiers Names and Code). However the existing researches resolve the problem manually. The manual process does not work when the size of data is enormous. The paper proposes a novel automatic LOINC mapping algorithm which uses indexing techniques and semantic similarity analysis of medical information. They use file system which is not proper to enormous medical data. We designed and implemented mapping algorithm for standardization laboratory codes in medical informatics compared with the existing researches that are only proposed algorithms. The automatic creation of searching words is being possible. Moreover, the paper implemented medical searching framework based on database system that is considered large size of medical data.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.184-191
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• 2022

This study aims to provide basic information necessary to find an efficient management plan for patients using auto insurance. The analysis was conducted on the five-year auto insurance medical expenses review data registered in the health care bigdata Hub from 2016 to 2020. As a result of the analysis, the number one composition ratio of auto insurance inpatient treatment expenses was treatment and surgery fees for Certified tertiary hospitals, hospitalization fees for general hospitals, hospitals and clinics, and treatment and surgery fees for oriental medical institutions and dental hospitals. outpatient treatment expenses was doctor's fee for medical institution, treatment and surgery fees for oriental medical institutions and dental hospitals. The ratio of medication, anesthesia, and special equipment significantly affected the cost of inpatient. And the ratio of physical therapy significantly affected the cost of outpatient.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1551-1554
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• 2003

최근 다양한 의료정보 시스템이 개발되어, 그 사용이 급증하고 있다. 이 들 각각의 의료정보 시스템에서 발생, 축적된 의료정보는 분산 이질의 형태를 가지며, 또한 같은 의미를 갖는 의료정보가 각기 다른 구조와 용어로 기술되어 축적되는 것이 일반적이다. 이와 같이 개별적으로 개발, 활용되어 온 의료정보를 웹 상에서 통합하여, 단일화 된 의료정보 검색 기능을 제공하기 위해서는 이들 의료정보의 의미적 연관성을 고려한 정보의 통합, 검색 기술의 개발이 필수적이다. 본 논문에서는 의미적 의료정보의 통합을 위한 UMLS와 LOINC 데이터베이스 기반의 연관 값 지식베이스의 설계 및 개발 방식을 제안한다. 웹 상에 존재하는 각종 분산 이질 형태의 의료정보는 XML을 공통 데이터 구조로 하여 통합되며, 정보 통합의 과정에서 연관 값 지식베이스를 참조하여 의미적 관련도가 높은 의료정보(구조 정보와 내용 정보)는 상호 연결되어, 진정한 의미의 정보 통합을 구현하게 된다. 지식베이스는 용어별로 식별자, 요소명, 연관값, 복수형, 동의어, 한글 이름 등의 필드틀 가지며, 현재 상담, 처방, 보험, 의료용어, 증상, 임상결과 등 적용분야 별로 작성된 연관 값 지식베이스가 구현되어 있다.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.88-94
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• 2008

This paper is proposed that ontology_based Oriental Medicine Customer Relationship Management system is designed with existing OCS, EMR, ERP system for oriental medicine center of efficient customer information management and analysis. As using ontology technique, we support oriental medicine service at grade according to quality and healthy of the customer. Also we designed 4 kind oriental medicine customer relationship management system frame - customer management, public relations/marketing, service management, statistics/analysis - in the customer management process standardization through a medical expert system.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.904-905
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• 2023

본 논문에서는 의료 영상 생성을 위한 Med-StyleGAN2를 제안한다. 생성적 적대 신경망은 이미지 생성에는 효과적이지만, 의료 영상 생성에는 한계점을 가지고 있다. 따라서 본 연구에서는 의료 영상 생성에 특화된 StyleGAN 기반 학습 모델을 제안한다. 이는 다양한 의료 영상 어플리케이션에 활용할 수 있으며, 생성된 의료 영상에 대한 정량적, 정성적 평가를 수행함으로써 의료 영상 생성 분야의 발전 가능성에 대해 연구한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.511-522
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• 2020

The purpose of this thesis is to derive a strategy to establish an ecosystem for promoting health my data projects in the public domain. To this end, first, the types of my data business were classified by business domain, subject, purpose, and method, and based on this, my data business being promoted in Korea and abroad was analyzed by type. After that, based on the analysis results, scenarios for my data projects that public domain can promote and the roles and major issues of each subject were identified, and the strategic direction for each subject of the ecosystem was presented. Such an attempt is of primary significance in revealing the role that the health MyData project can take the lead in the public domain to settle in Korea targeting sensitive information. Through this, it is expected that it will be a cornerstone of discussion to identify issues that are expected to establish an ecosystem in Korea, and to present a direction in which the my data business can be promoted in the right direction in the future.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.2
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• pp.51-73
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• 2022

Currently, an implementation plan of administrative information dataset record management has been prepared; however, analyzing the specificity of various administrative information systems and preparing a reasonable level of management reference table by applying about 1.3% (EA portal registration system: 16,199, consulting system: 214) has its limitations. This study started by recognizing the importance of the records management environment in administrative information datasets. Based on the described information, the current records management environment was analyzed by dividing the six areas of the management reference table of the picture archiving and communication system (PACS) into three groups. Thus, a systematic environmental improvement model was proposed, enhancing the effectiveness of dataset records management in the field. Although there is a limitation in analyzing one of the dataset records management environments of various institutions, it is intended to help broaden the horizons of records management research.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.65-72
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• 2010

Nowadays, most hospitals have been used to create MRI or CT and managed them. Doctors depend on fast access to images such as magnetic resonance imaging (MRIs), computerized tomography (CT) scans, and X-rays for accurate diagnoses. Those image data are related privacy of a patient. Therefore, it should be protected from hackers and managed perfectly. In this paper, we propose a data hiding method into MRI or CT related a condition and intervention of a patient, and it is suggested that how to authenticate patient information from an image. In this way, we create hash code using HMAC with patient information, and hash code and patient information is hided into an image. After then, doctor will check authentication using HMAC. In addition, we use a reversible data hiding DE(Difference Expansion) algorithm to hide patient information. This technique is possible to reconstruct the original image with stego image. Therefore, doctor can easily be possible to check condition of a patient. As a consequence of an experiment with MRI image, data hiding, extraction and reconstruct is shown compact performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.281-282
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• 2014

병의원에서 다양한 정보시스템을 도입하면서 환자들과 관련된 방대한 의료 데이터들이 전자적인 형태로 축적되어 왔고, 최근에는 의료진이나 환자에게 적절한 정보를 제공하는데 이러한 데이터를 활용하고자 하는 노력이 이어지고 있다. 그러나 의료 데이터는 분량이 방대하고 전문적인 내용을 다루기 때문에 이에 기반한 정보를 개인 환자에게 제공하는데 있어서는 데이터에 포함된 내용을 사용자의 이해가 편리한 형태로 가공하는 것이 중요하다. 이에 본 논문에서는 연관분석과 관련된 행렬 기반 표현 방법을 기반으로 한 하이브리드 시각화 방법을 개발하고, 이를 건강검진 결과에 적용하는 것을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.840-842
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• 2012

오늘날의 정보통신 환경은 유비쿼터스 IT기술의 시대로 진입하고 있다. 유비쿼터스는 사용자가 컴퓨터나 네트워크를 의식하지 않은 상태에서 시간과 장소에 구애받지 않고 자유롭게 네트워크에 접속 할 수 있는 정보와 환경을 의미한다. u-Health(Ubiquitous-Health)는 의료 및 국민 복지에서 떠오르는 분야이며 기존의 의료서비스와는 달리 사용자가 간편하고 언제 어디서나 사용될 수 있는 시스템이다. 기존 u-Health 시스템은 사용자가 착용한 센서로부터 신체 데이터를 제공받고, 제공 받은 데이터로 사용자가 현재 어떠한 상태인지를 파악한다. 그러나 센서로부터 제공받은 신체데이터는 무선통신으로 인한 데이터의 손실 및 오류가 발생하게 된다. 이러한 단점을 극복하고 정확한 환자의 상태를 판단하기 위한 방법으로 온톨로지 기반의 상황인식을 적용하여 기존의 u-Health 시스템 보다 더욱 신뢰성 있는 u-Health 시스템을 구축하고자 한다.