• 대한의생명과학회지
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• 제10권4호
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• pp.485-493
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• 2004

In the current field of Medical Informatics, the information increases, and changes fast, so we can access the various data types which are ranged from text to image type. A small number of technician digitizes these data to establish database, but it is needed a lot of money and time. Therefore digitization by many end-users confronting data and establishment of searching database is needed to manage increasing information effectively. New data and information are taken fast to provide the quality of care, diagnosis which is the basic work in the medicine. And also It is needed the medical database for purpose of private study and novice education, which is tool to make various data become knowledge. However, current medical database is used and developed only for the purpose of hospital work management. In this study, using text input, file import and object images are digitized to establish database by people who are worked at the medicine field but can not expertise to program. Data are hierarchically constructed and then knowledge is established using a tree type database establishment method. Consequently, we can get data fast and exactly through search, apply it to study as subject-oriented classification, apply it to diagnosis as time-depended reflection of data, and apply it to education and precaution through function of publishing questions and reusability of data.

• 산경연구논집
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• 제13권11호
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• pp.1-10
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• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.345-352
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• 2022

Conducting AI-based fusion business due to the increment of ICT fusion medical device has been expanded. In addition, AI-based medical devices help change existing medical system on treatment into the paradigm of customized treatment such as preliminary diagnosis and prevention. It will be generally promoted to the change of medical device industry. Although the current demand forecasting of medical biotechnology commercialization is based on the method of Delphi and AHP, there is a problem that it is difficult to have a generalization due to fluctuation results according to a pool of participants. Therefore, the purpose of the paper is to predict demand forecasting for identifying promising technology based on building up big data in medical biotechnology. The development method is to employ candidate technologies of keywords extracted from SCOPUS and to use word2vec for drawing analysis indicator, technological distance similarity, and recommended technological similarity of top-level items in order to achieve a reasonable result. In addition, the method builds up academic big data for 5 years (2016-2020) in order to commercialize technology excavation on demand perspective. Lastly, the paper employs global data studies in order to develop domestic and international demand for technology excavation in the medical biotechnology field.

• 디지털콘텐츠학회 논문지
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• 제4권1호
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• pp.57-66
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• 2003

본 논문에서는 인터넷 기반에서의 3자(환자, 의사, 약사)간의 상호대화형 원격진료 시스템 구현으로서, 효율적인 진료와 빠른 처리를 위한 전자진료차트 및 자료처리에 관한 내용을 제시하고 있다. 즉, 고가형 시스템, 비호환성 등 기존 원격진료시스템의 문제점을 해결한 저가형이면서, 누구나 참여할 수 있는 웹상에서의 시공간을 초월한 on-line 및 off-line 겸용모드의 지능형 원격진료시스템이다. 데이터베이스는 IIS 4.0 웹서버상에서 ASP와 SQL을 연동한 구현하여 효율적인 자료처리를 위한 시스템 통합과 환자와 의사간의 on-line 상담, 그리고 off-line상에서의 진료와 환자가 지정한 약사로의 처방전 전송 및 조제, 그리고 진료데이터의 저장 및 검색으로 인한 반영구적인 진료데이터저장, 환자 및 의사의 본 진료데이터를 이용한 보다 정확한 진료 및 처방등이 가능하다.

• 한국인터넷방송통신학회논문지
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• 제12권5호
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• pp.39-54
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• 2012

오늘날 의료정보화 수준향상과 디지털 병원화의 흐름에 따라 PACS는 의료기관의 핵심 인프라 중 하나로 자리매김하였다. 이와 함께 생산되는 디지털 의료영상의 종류 및 의료영상 데이터가 양적으로 급증하고 있으며, 이는 의료영상 데이터의 효과적인 보관을 위한 의료영상 압축을 중요한 요소로 부각시킨다. 현재 의료영상에 관한 사실상의 표준인 DICOM 규격에서는 의료영상 압축을 위하여 무손실 압축기법인 RLE를 명시하고 있으나, 무손실 범용 압축기법인 RLE는 인체의 대칭성을 가지는 많은 의료영상에 적용하면 높은 압축율 기대하기 힘들다. 이 논문에서는 다양한 의료영상 중 대칭 특성을 크게 내포하는 뇌 CT 영상을 대상으로 하여 영상 내 관심영역을 검출하고 대칭특성에 따라 영상의 픽셀 값을 재코딩하는 전처리 하고 영상을 압축하는 기법을 제안한다. 실험에 의하면, 제안한 기법은 RLE 압축과 영상 내 관심영역을 검출하지 않고 압축할 때와 비교하여 높은 압축률을 보인다.

• 디지털융복합연구
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• 제12권2호
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• pp.397-407
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• 2014

의료정보의 급속한 발달로 인하여 막대한 양의 정보가 쌓이고 있다. 이러한 정보를 이용하여 임상연구를 하고자하는 욕구가 늘고 있으며, 고령화와 의료비의 가파른 상승을 해결해야하는 문제에 직면해 있다. 이에 대한 대안으로 빅데이터의 활용에 대한 목소리가 높다. 본 연구는 우리나라 의료기관들의 정보화 현황을 살피고 빅데이터 활용방안에 대한 정책적 시사점을 제공하고자 한다. 문헌조사와 의료기관의 의료정보전문가 면담을 통해 자료를 수집하였으며, 수집기간은 2013년 9월부터 2013년 11까지 4개월간 시행하였다. 연구결과 향후 병원정보시스템은 환자관리 및 행정에서 연구와 정보전략 측면으로 발전하고 있다. 따라서 빅데이터 활용을 위한 시스템 구축과 비정형 데이터의 효과적 활용을 고려하여 전문인력 양성과 더불어 의료비 절감을 위한 국가의 정책지원이 마련되어야 할 것이다.

• 대한의용생체공학회:의공학회지
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• 제26권5호
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• pp.301-307
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• 2005

We introduce a new multimedia telemedicine system which is called Telemedicine for Real-time Emergency Multi-consultation(TREM), based on multiple connection between medical specialists. Due to the subdivision of medical specialties, the existing one-to-one telemedicine system needs be modified to a simultaneous multi-consulting system. To facilitate the consultation the designed system includes following modules: high-quality video, video conferenceing, bio-signal transmission, and file transmission. In order to enhance the operability of the system in different network environment, we made it possible for the user to choose appropriate data acquisition sources of multimedia data and video resolutions. We have tested this system set up in three different places: emergency room, radiologist's office, and surgeon's office. All three communicating systems were successful in making connections with the multi-consultation center to exchange data simultaneously in real-time.

• 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.

• Communications for Statistical Applications and Methods
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• 제27권2호
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• pp.225-239
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• 2020

Analysis approaches for single compositional data are well established; however, effective analysis strategies for paired compositional data remain to be investigated. The current project was motivated by studies of age-related hearing loss (presbyacusis), where subjects are classified into four audiometric phenotypes that need to be ranked within these phenotypes based on their paired compositional data. We address this challenge by formulating this problem as a classification problem and integrating a penalized multinomial logistic regression model with compositional data analysis approaches. We utilize Elastic Net for a penalty function, while considering average, absolute difference, and perturbation operators for compositional data. We applied the proposed approach to the presbyacusis study of 532 subjects with probabilities that each ear of a subject belongs to each of four presbyacusis subtypes. We further investigated the ranking of presbyacusis subjects using the proposed approach based on previous literature. The data analysis results indicate that the proposed approach is effective for ranking subjects based on paired compositional data.

• 융합정보논문지
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• 제9권2호
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• pp.1-6
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• 2019

본 논문에서는 의료용 빅 데이터를 활용하여 비즈니스와 연계하여 새로운 서비스를 창출하기 위한 프레임 워크를 설계하였다. 단순한 데이터 분석 단계를 나타내는 것이 아니라 데이터의 활용 목적을 명확히 하고, 이에 대한 분석을 수행하여 그 속에서 가치를 추출하고 실제 사업이나 서비스를 운용할 때까지의 과정을 설계한다. 설계된 프레임워크는 기본 아키텍처, 사회 시스템 모델까지 커버할 수 있도록 하였다. 설계된 프레임 워크를 참조하여 사회 시스템에 적용될 수 있도록 디자인하였으며, 기본 데이터로는 의료용 빅 데이터를 중심으로 하였다. 의료용 기본 데이터를 적용한 프레임 워크 설계로 여러 의료용 사업 제휴 및 서비스 창출을 실현할 수 있을 것으로 기대하고 있다.