• Genomics & Informatics
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• 제18권2호
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• pp.17.1-17.4
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• 2020

The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. However, these patient communities are especially active on social media. Data from social media could serve as a source of patient-centric knowledge for these diseases complementary to the information collected in clinical settings and patient registries, and may also have potential for research use. To explore this question, we attempted to extract patient-centric knowledge from social media as a task for the 3-day Biomedical Linked Annotation Hackathon 6 (BLAH6). We selected amyotrophic lateral sclerosis and multiple sclerosis as use cases of rare and intractable diseases, respectively, and we extracted patient histories related to these health conditions from Twitter. Four diagnosed patients for each disease were selected. From the user timelines of these eight patients, we extracted tweets that might be related to health conditions. Based on our experiment, we show that our approach has considerable potential, although we identified problems that should be addressed in future attempts to mine information about rare/intractable diseases from Twitter.

• 로봇학회논문지
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• 제3권1호
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• pp.58-67
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• 2008

This study developed a novel augmented reality interface for minimally invasive surgery. The augmented reality technique can alleviate the sensory feedback problem inherent to laparoscopic surgery. An augmented reality system merges real laparoscope image and reconstructed 3D patient model based on diagnostic medical image such as CT, MRI data. By using reconstructed 3D patient model, AR interface could express structure of patient body that is invisible outside visual field of laparoscope. Therefore, an augmented reality system improved sight information of limited laparoscope. In our augmented reality system, the laparoscopic view is located at the center of a wide-angle concave screen and reconstructed 3D patient model is displayed outside the laparoscope. By using a joystick, the laparoscopic view and the reconstructed 3D patient model view are changed concurrently. With our augmented reality system, the surgeon can see the peritoneal cavity from a wide angle of view, without having to move the laparoscope. Since the concave screen serves immersive environments, the surgeon can feel as if she is in the patient body. For these reasons, a surgeon can recognize easily depth information about inner parts of patient and position information of surgical instruments without laparoscope motion. It is possible for surgeon to manipulate surgical instruments more exact and fast. Therefore immersive augmented reality interface for minimally invasive surgery will reduce bodily, environmental load of a surgeon and increase efficiency of MIS.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.326-329
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• 2009

기존의 Nurse Call 제품은 환자가 비상 call을 하였을 때 환자의 이름과 병실만 간호사의 단말기에 표시되므로, 환자가 병실이 아닌 다른 장소에 있는 경우에는 환자의 위치를 찾기가 어려운 상황이다. 따라서 환자가 병실이 아닌 다른 장소에서 긴급 call을 하는 경우에는 환자의 위치를 알 수 없어 찾는데 많은 시간을 소요할 수가 있어 위급한 환자에게는 큰 타격을 줄 수 있다. 따라서 본 논문에서는 SOFM을 이용하여 중계기를 최적으로 배치하고 배치한 정보와 RSSI를 이용하여 환자의 위치를 찾아낼 수 있는 무선 너스 콜 시스템을 제안하였다. 제안한 시스템의 유용성을 확인하기 위하여 실험한 결과 위치 정보를 오차 범위 내에서 얻을 수 있었다.

• 대한의용생체공학회:의공학회지
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• 제24권6호
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• pp.533-541
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• 2003

본 논문은 환자 진료정보 공유 시 환자의 개인 및 진료 정보 보호 문제점을 해결하기 위해서 여러 장의 진찰카드를 하나의 IC카드로 통합하기 위한 시스템을 개발하였다. 먼저, 진료정보 공유를 위한 최소데이터세트를 정의하였고, 이 최소데이터세트를 통합 병원 진찰 IC 카드에 구현하고 발급할 수 있는 발급 시스템을 개발했다. 환자의 개인정보 보안 및 인증을 위해서는 윈도우 2000 기반 전자서명 인증센터를 구축하고 3-DES 적용한 IC 카드 기반의 통합 병원 진찰 IC 카드를 개발했다. 기존 병원 전산시스템과 효율적인 연동을 위한 통합 병원 진찰 IC 카드에 의한 진료접수/예약 시스템을 개발했다. 본 연구에서 개발한 통합 병원 진찰 IC 카드 시스템을 11개 병원에서 1.000명의 환자에게 적용한 결과, 시범 대상 병원들의 환자 진료 접수/예약뿐 아니라 정보 공유의 안정적 확장을 도모할 수 있는 기반을 마련할 수 있었다.

• 보건의료생명과학 논문지
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• 제9권1호
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• pp.1-9
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• 2021

본 연구에서는 한국보건의료정보원에서 실시하는 EMR 인증기준울 이해할 수 있도록 보건의료정보관리 실습 프로그램에 인증기준을 추가한 모델을 연구하여 제시하였다. 실습 프로그램은 EMR 인증제의 기능성 기준에 해당하는 환자정보관리를 실습하고 이해할 수 있도록 보건의료정보관리 교육시스템에 환자정보관리에 대한 인증기준 기능을 추가하였다. 환자정보관리를 위한 EMR 인증기준 실습프로그램은 다음과 같은 인증기준으로 구성되었다. 등록번호 및 인적사항 관리, 진료예약 일정관리, 인적사항 수정이력관리, 동명이인 구분자 표시, 다중 등록번호 통합관리, 식별정보를 이용한 환자 검색, 진료형태에 따른 환자 검색, 수술시술 동의서 기록·조회, 개인정보활용동의서 기록·조회, 연명의료결정정보 표시, 외부 의료기관문서 등록·조회, 외부 검사결과 등록·조회. 이와 같이 인증기준에 의한 보건의료정보시스템의 기능을 운영하여 실습해봄으로써 인증기준의 기능성 영역에서 환자정보관리의 인증기준과 내역을 이해하고 실습할 수 있다. EMR 인증 기준에 맞춰 환자정보관리 실습을 수행해봄으로써 전자의무기록시스템에서의 표준화된 환자정보관리를 이해할 수 있다. 또한 EMR 인증기준의 기능을 확인할 수 있기 때문에 의료기관에서 보건의료정보관리사의 전자의무기록시스템의 관리 능력을 향상시킬 수 있을 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.967-979
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• 2013

Now a day, Wireless Sensor Networks (WSNs) are being widely used in different areas one of which is healthcare services. A wireless medical sensor network senses patient's vital physiological signs through medical sensor-nodes deployed on patient's body area; and transmits these signals to devices of registered medical professionals. These sensor-nodes have low computational power and limited storage capacity. Moreover, the wireless nature of technology attracts malicious minds. Thus, proper user authentication is a prime concern before granting access to patient's sensitive and private data. Recently, P. Kumar et al. claimed to propose a strong authentication protocol for healthcare using Wireless Medical Sensor Networks (WMSN). However, we find that P. Kumar et al.'s scheme is flawed with a number of security pitfalls. Information stored inside smart card, if extracted, is enough to deceive a valid user. Adversary can not only access patient's physiological data on behalf of a valid user without knowing actual password, can also send fake/irrelevant information about patient by playing role of medical sensor-node. Besides, adversary can guess a user's password and is able to compute the session key shared between user and medical sensor-nodes. Thus, the scheme looses message confidentiality. Additionally, the scheme fails to resist insider attack and lacks user anonymity.

• 한국전자통신학회논문지
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• 제2권4호
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• pp.244-249
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• 2007

HL7은 병원정보 시스템에서 사용되는 정보와 관련된 표준화된 프로토콜이다. Central Monitor로부터 전송되어진 환자의 생체정보 Raw Data가 HIS의 데이터 수신 모듈을 통해 사용가능한 데이터로 재구성될 수 있도록 설계가 이루어져 있다. 환자 생체정보에 대한 실시간성과 생체정보에 대한 생체정보 데이터의 연속성을 부여함으로서 베드 사이트의 환자에게서 발생된 모든 생체정보에 의해 환자 관리가 이루어진다. 또한 보다 많은 검사장비의 데이터를 데이터베이스를 이용하여 전산화함으로서 해당 환자의 광범위한 자료 검색이 이루어지므로 획기적인 원격진료로 활용이 가능하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2772-2786
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• 2022

We had researched an automatic authentication-supported medical information platform[6]. The proposed automatic authentication consists of user authentication and mobile terminal authentication, and the authentications are performed simultaneously in patients' emergency conditions. In this paper, we studied on finding emergency conditions for the automatic authentication by applying big data processing and AI mechanism on the extended medical information platform with an added edge computing system. We used big data processing, SVM, and 1-Dimension CNN of AI mechanism to find emergency conditions as authentication means considering patients' underlying diseases such as hypertension, diabetes mellitus, and arrhythmia. To quickly determine a patient's emergency conditions, we placed edge computing at the end of the platform. The medical information server derives patients' emergency conditions decision values using big data processing and AI mechanism and transmits the values to an edge node. If the edge node determines the patient emergency conditions, the edge node notifies the emergency conditions to the medical information server. The medical server transmits an emergency message to the patient's charge medical staff. The medical staff performs the automatic authentication using a mobile terminal. After the automatic authentication is completed, the medical staff can access the patient's upper medical information that was not seen in the normal condition.

• 한국의료질향상학회지
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• 제26권2호
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• pp.56-65
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• 2020

Purpose:This study aims to understand and explore the subjective experiences of patient safety education among health care professionals in developing a patient safety curriculum in South Korea. Methods: A qualitative descriptive study was conducted through two focus group interviews in the period October-December 2018. Eleven participants who underwent patient safety education participated in each session. All interviews were recorded and transcribed as spoken, and qualitative content analysis was used to identify categories of discussion depicting participants' subjective experience with patient safety education. Results: A total of three categories and seven themes were identified out of 77 units of analysis. Topics were identified in the dimensions of a patient safety curriculum, as follows: (1) activities for patient safety; (2) principle of patient safety (five rights, ethics, patient participation) and patient participation; (3) leadership, teamwork, and communication; and (4) reporting and learning system for patient safety events. In the dimension of methods, (5) case and evidence-based education and (6) multidisciplinary and small group teaching were identified. Finally, in the dimension of the system, (7) policies for patient safety education were identified. Conclusion: Our findings indicate that patient safety education is a significant area for health care professionals. Health care professionals suggested that a systematic patient safety curriculum would improve their knowledge and attitude toward patient safety. Moreover, it enables them to better construct a safety environment in a hospital.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.225-234
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• 2023

In this era of information and communication technology (ICT), tremendous improvements have been witnessed in our daily lives. The impact of these technologies is subjective and negative or positive. For instance, ICT has brought a lot of ease and versatility in our lifestyles, on the other hand, its excessive use brings around issues related to physical and mental health etc. In this study, we are bridging these both aspects by proposing the idea of AI based mental healthcare (AIMS). In this regard, we aim to provide a platform where the patient can register to the system and take consultancy by providing their assessment by means of a chatbot. The chatbot will send the gathered information to the machine learning block. The machine learning model is already trained and predicts whether the patient needs a treatment by classifying him/her based on the assessment. This information is provided to the mental health practitioner (doctor, psychologist, psychiatrist, or therapist) as clinical decision support. Eventually, the practitioner will provide his/her suggestions to the patient via the proposed system. Additionally, the proposed system prioritizes care, support, privacy, and patient autonomy, all while using a friendly chatbot interface. By using technology like natural language processing and machine learning, the system can predict a patient's condition and recommend the right professional for further help, including in-person appointments if necessary. This not only raises awareness about mental health but also makes it easier for patients to start therapy.