• 전자공학회논문지CI
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• 제49권1호
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• pp.46-53
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• 2012

WBAN(Wireless Body Area Network) 기술은 인체 내부 및 외부에 부착한 디바이스들을 무선으로 연결하여 통신할 수 있는 근거리 무선 통신 기술로서 IEEE 802.15.6 TG BAN을 중심으로 물리 계층, 데이터 링크 계층, 네트워크 계층 및 응용계층 등에서 표준화가 진행되고 있다. WBAN 환경을 지원하기 위해서는 센서 노드 디바이스 뿐만 아니라 WBAN 미들웨어 및 WBAN 응용 서비스 등의 WBAN 핵심 기술의 개발이 필요하다. 본 논문에서는 3G, 4G, WiFi를 통하여 환자의 생체 정보를 정확하고 신속하게 전달하기 위한 목적으로 WBAN 환경을 위한 의료용 메시지 구조를 설계하고 WBAN 게이트웨이 관리 엔진을 통하여 BN으로부터 들어온 환자의 생체 정보를 스마트폰에서 확인할 수 있는 의료용 애플리케이션을 구현하였다.

• 대한디지털의료영상학회논문지
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• 제12권2호
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• pp.103-111
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• 2010

A total of 200 hospital employees participated in this study from January 2009 to June 2010. For the survey, each participant was given necessary items for external health exams. Cronbach's alpha was calculated for the survey regarding wireless networks. There was a need for educating data processing workers in the medical field regarding fundamental information prior to wireless network construction. The reason is high scores would be collected, which would reflect knowledge regarding data processing used at hospitals and the differences between paper charts and electronic charts. However, low scores were obtained which reflected knowledge regarding the differences between wired and wireless networks and Mini-PACS. Time for each patient was shortened to a maximum of three minutes and minimum of one minute for treatment and transmitting medical images when comparing pre and post wireless network construction(p < 0.01). Scores from the pre and post construction survey increase 1.98, 1.65, and 1.43 points for activity in the health screening area, usage of space in the health screening vehicle, and patient information storage respectively(p < 0.05). The number of patients receiving external health screenings twelve times was 3,655 prior to construction of a wireless network system. However, the number increased to 4,265 after construction. The increasing percentage was 17% in total. Prior to construction, X-ray images were taken 527 times, but after construction of a wireless network, this number growed to 1,194 and it was 116% increase. The loss of patient's medical treatment charts was reduced from 19.8% to 18.7% after construction. We believe that educating medical workers on Mini-PACS and Mini-OCS Systems will not only increase their efficiency but also make patients receiving better treatment.

• Spatial Information Research
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• 제4권1호
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• pp.43-54
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• 1996

응급의료체계의 있어서 가장 중요한 분야중의 하나는 응급환자를 병원단계까지 후송하는 응급 후송체계의 개선이라 할 수 있는데 이와 같은 응급후송체계의 개선을 위하여 GIS기법을 이용하여 시스템을 개발하였다. 본 연구에서 시범 지역으로 강남구과 송파구를 대상으로 PC ARC/INFO를 이용하여 스시템을 구축하였는데 시스템의 기본기능은 환자발생신고가 접수되면 환자의 위치 및 가장 가까운 응급출동기관의 위치, 후송예정 병원의 위치를 분석하여 지도상에 표시하고, 표시된 위치들의 최단경로를 찾을 수 있는 기능과 선정된 응급출동기관과 병원의 상세정보를 볼 수 있는 기능을 갖고 있다.

• 대한한방내과학회지
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• 제43권6호
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• pp.1075-1088
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• 2022

Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2458-2482
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• 2023

Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, MultiHead Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.

• 대한의용생체공학회:의공학회지
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• 제15권2호
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• pp.121-128
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• 1994

In this paper, MIlS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemnted system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression! decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.489-491
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• 2002

The need for video diagnosis in medicine has been increased and real-time transfer of digital video will be an important component in PACS and telemedicine. But, Network environment has certain limitations that the required throughput can not satisfy quality of service (QoS). MPEG-4 ratified as a moving video standard by the ISO/IEC provides very efficient video coding covering the various ranges of low bit-rate in network environment. We implemented MPEG-4 CODEC (coder/decoder) and applied various compression ratios to moving ultrasound images. These images were displayed in random order on a client monitor passed through network. Radiologists determined subjective opinion scores for evaluating clinically acceptable image quality and then these were statistically processed in the t-Test method. Moreover the MPEG-4 decoded images were quantitatively analyzed by computing peak signal-to-noise ratio (PSNR) to objectively evaluate image quality. The bit-rate to maintain clinically acceptable image quality was up to 0.8Mbps. We successfully implemented the adaptive throughput or bit-rate relative to the image quality of ultrasound sequences used MPEG-4 that can be applied for diagnostic performance in real-time.

• 디지털융복합연구
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• 제20권5호
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• pp.681-693
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• 2022

본 연구는 근골격계 질환으로 입원한 환자의 의무기록지 키워드 네트워크 분석을 통해 근골격계와 관련된 표준의료용어를 유추하여 보건의료현장의 비정형화된 데이터 활용 방안을 제시하기 위함이다. 분석 대상은 2010년부터 2019년까지 근골격계 질환 환자의 입퇴원요약지 145부로, 더아이엠씨(The IMC)에서 개발한 빅데이터 분석 솔루션인 TEXTOM을 활용하여 분석하였다. 1차·2차 정제과정을 통해 도출된 177개의 근골격계 관련 용어를 최종 분석하였다. 연구결과 다빈도 용어는 'Metastasis', 의료용어 체계별 분석 결과에서 임상소견은 'Metastasis', 증상은 'Weakness', 진단은 'Hepatitis', 처치는 'Remove', 신체구조는 'Spine', 약물은 'Oxycodone'이 가장 많이 사용되었다. 이러한 결과를 바탕으로 정형화되지 않은 의료데이터의 분석과 활용 및 관리 방안에 대한 시사점을 제안하고자 한다.

• 대한방사선기술학회지:방사선기술과학
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• 제43권3호
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• pp.195-208
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• 2020

Artificial intelligence(AI) is a field of computer science that is defined as allowing computers to imitate human intellectual behavior, even though AI's performance is to imitate humans. It is grafted across software-based fields with the advantages of high accuracy and speed of processing that surpasses humans. Indeed, the AI based technology has become a key technology in the medical field that will lead the development of medical image analysis. Therefore, this article introduces and discusses the concept of deep learning-based medical imaging analysis using the principle of algorithms for convolutional neural network(CNN) and back propagation. The research cases application of the AI based medical imaging analysis is used to classify the various disease(such as chest disease, coronary artery disease, and cerebrovascular disease), and the performance estimation comparing between AI based medical imaging classifier and human experts.

• 인터넷정보학회논문지
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• 제18권6호
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• pp.75-84
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• 2017

As there has been growing interests in PHR-based personalized health management project, various institutions recently explore safe methods of recording personal medical and health information. In particular, innovative medical solution can be realized when medical researchers and medical service institutes can generally get access to patient data. As EMR data is extremely sensitive, there has been no progress in clinical information exchange. Moreover, patients cannot get access to their own health data and exchange it with researchers or service institutions. It can be operated in terms of technology, yet policy environment are affected by state laws as well as Privacy and Security Policy. Blockchain technology-independent, in transaction, and under test-is introduced in the medical industry in order to settle these problems. In other words, medical organizations can grant preliminary approval on patient information exchange by using the safely encrypted and distributed Blockchain ledger and can be managed independently and completely by individuals. More apparently, medical researchers can gain access to information, thereby contributing to the scientific advance in rare diseases or minor groups in the world. In this paper, we focused on how to manage personal medical information and its protective use and proposes medical treatment exchange system for patients based on a permissioned Blockchain network for the safe PHR operation. Trusted Model for Sharing Medical Data (TMSMD), that is proposed model, is based on exchanging information as patients rely on hospitals as well as among hospitals. And introduce medical treatment exchange system for patients based on a permissioned Blockchain network. This system is a model that encrypts and records patients' medical information by using this permissioned Blockchain and further enhances the security due to its restricted counterfeit. This provides service to share medical information uploaded on the permissioned Blockchain to approved users through role-based access control. In addition, this paper presents methods with smart contracts if medical institutions request patient information complying with domestic laws by using the distributed Blockchain ledger and eventually granting preliminary approval for sharing information. This service will provide an independent information transaction and the Blockchain technology under test will be adopted in the medical industry.