• Progress in Medical Physics
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• v.17 no.3
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• pp.144-152
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• 2006

The telemedicine using independent client-server system via networks can provide high quality normalized services to many hospitals, specifically to local/rural area hospitals. This will eventually lead to a decreased medical cost because the centralized institute can handle big computer hardware systems and complicated software systems efficiently and economically, Customized cancer radiation treatment planning for each patient Is very useful for both a patient and a doctor because it makes possible for the most effective treatment with the least possible dose to patient. Radiation planners know that too small a dose to the tumor can result in recurrence of the cancer, while too large a dose to healthy tissue can cause complications or even death. The best solution is to build an accurate planning simulation system to provide better treatment strategies based on each patient's computerized tomography (CT) image. We are developing a web-based and a network-based customized cancer radiation therapy simulation system consisting of four Important computer codes; a CT managing code for preparing the patients target data from their CT image files, a parallel Monte Carlo high-energy beam code (PMCEPT code) for calculating doses against the target generated from the patient CT image, a parallel linear programming code for optimizing the treatment plan, and scientific data visualization code for efficient pre/post evaluation of the results. The whole softwares will run on a high performance Beowulf PC cluster of about 100-200 CPUs. Efficient management of the hardware and software systems is not an easy task for a hospital. Therefore, we integrated our system into the client-sewer system via network or web and provide high quality normalized services to many hospitals. Seamless communication with doctors is maintained via messenger function of the server-client system.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.606-611
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• 2007

최근 u-healthcare 서비스 분야에서 단일 시점의 일반화된 치료가 아닌 장시간 개개인의 특성이 반영된 진료와 의료 서비스에 대한 관심이 증가하고 있다. 그러나 기존의 생체 신호 해석은 임상적인 실험을 통해 얻은 표준화된 임계치를 이용해 분석하는 일관된 판단 방법이 주를 이루었다. 본 논문에서는 미래형 홈 환경에서 사용자에 따라 다른 신호 해석을 지원하는 사용자 적응적 생체 신호 해석 방법을 제안한다. 생체 신호 해석은 사용자의 컨텍스트와 환경 컨텍스트를 통합하는 모듈과, 지식표현 기법을 적용한 개인화된 추론 모듈로 구성된다. 제안된 방법은 사용자 정황 정보를 고려하여 사용자 적응적인 생체 신호 해석을 지원하며, 환경 컨텍스트를 고려하여 환경의 변화에 영향을 최소화하는 생체 신호 해석을 지원한다. 또한 사상의학 이론을 생체신호 해석에 동적으로 적용할 수 있는 틀을 제공한다. 이는 추후 미래형 홈 환경에서 다양한 종류의 센서와 함께 개인화된 맞춤형 재택 건강관리 서비스에 활용할 수 있다.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.125-128
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• 2008

사상의학은 개인별 체질의 분류에 따른 맞춤형 의학으로 우리나라 고유의 독특한 전통 의학이다. 이와 같은 사상의학에서 가장 중요하게 여겨지는 것이 사상체질의 정확한 분류이다. 따라서 사상체질 분류에 대한 객관적 요소의 확보 및 진단 지표 마련이 시급하게 해결되어야 할 과제이다. 이를 위해 본 논문에서는 사상체질 분류의 객관화, 정량화 및 시각화를 위해 얼굴 영상 신호와 음성 신호를 분석하여 결과값을 추출하고 체질별 집단군간의 차이점을 비교하여 사상체질 분류 시스템을 구현하고자 한다. 특히 영상 및 음성 신호는 성별, 연령별, 지역별 등의 구분에 따라 달라지기 때문에 본 논문에서는 40에서 50대 사이의 장년 여성을 대상으로 서울지역 거주자에 한해 사상체질 집단군을 구성하고 이들의 영상 및 음성 신호를 추출하여 체질간 비교, 분석을 수행하고자 한다. 최종적으로 실험을 통한 연구 결과의 유의성을 입증하고자 한다.

• Journal of agricultural medicine and community health
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• v.47 no.2
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• pp.67-77
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• 2022

Objective: This study was to evaluate the effectiveness of an individually tailored program based on self-measurement of blood glucose on health behavior and HbA1c in diabetes and pre-diabetes patients. Methods: The program consisted of seven sessions for 12 weeks which were carried out every two weeks. Almost all sessions were progressed on untact method except for the first and last session. The 71 subjects were assessed for their knowledge of diabetes, health behavior, the experience of self-measurement of blood glucose, body mass Index (BMI) and hemoglobin A1c (HbA1c) at before and after the program. They were also evaluated on their degree of utilization of blood glucose measurements after the program. Results: Each mean score on their knowledge of diabetes, health behavior and the experience of self-measurement of blood glucose was significantly increased from 14.77, 25.50, and 2.70 to 15.41, 28.40, and 4.81, respectively. Each mean score on both BMI and HbA1c (n=53) was significantly decreased from 24.47kg/m² and 7.27% to 24.01kg/m² and 6.67%, respectively. The post-HbA1c had a significant negative correlation(r=-0.415) with the degree of utilization of blood glucose measurements. The degree of utilization of blood glucose measurements had a significant positive correlation(r=0.581) with post-health behavior. Conclusions: The program shows effectiveness in improving HbA1c in Type 2 diabetes and pre-diabetes patients. The post-HbA1c might be related to the degree of utilization of blood glucose measurements which might be related to the health behavior.

• Information and Communications Magazine
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• v.32 no.11
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• pp.12-20
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• 2015

최근 의학 기술이 눈부시게 발전함에 따라 사람들은 수명이 연장되고 삶의 질 향상에 많은 관심을 가지게 되었다. 더욱이 혁신적인 디지털 기술 발전과 함께 다양한 웨어러블 기기와 수많은 헬스케어 어플리케이션이 출시되고 있으며, 이들은 어떻게 하면 개인의 성향이나 체질에 잘 맞는 맞춤형 (개인화) 서비스를 제공할 수 있을 것인가에 관심을 두고 진화하고 있다. 따라서 IoT 환경의 일상생활에서 입력되는 센서 데이터의 수집, 처리, 가공 기술, 일상 행위 및 라이프 스타일 인지, 지식 획득 및 관리 기술, 개인화 추천서비스 제공, 프라이버시 및 보안을 통합적으로 지원할 수 있는 프레임워크 개발에 대한 요구가 증대되고 있다. 이에 본 고에서는 저자가 개발중인 개인 맞춤 건강 및 웰니스 서비스를 제공하는 마이닝 마인즈 프레임워크를 소개한다. 마이닝 마인즈는 현존하는 최신 기술의 집약체로 개인화, 큐레이션, 빅 데이터 처리, 클라우드 컴퓨팅의 활용, 다양한 센서 정보의 수집과 분석, 진화형 지식의 생성과 관리, UI/UX를 통한 습관화 유도 등 다양한 요소를 포함한다. 그리고 건강 및 웰니스 프레임워크 요구사항 분석을 통해 마이닝 마인즈가 이러한 요구를 충족시킬 수 있으며, 개발된 프로토타입을 통해 개인화 서비스의 발전 가능성을 입증하고 향후 나아가야 할 방향을 제시한다.

• 한국노년학
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• v.31 no.1
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• pp.129-141
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• 2011

This study aims to find out effects of a tailored occupational activity program(TOAP) on the activities of daily living(ADL), cognitive function, depressive mood, and caregiver burden, who live in the community. Method : From October 2009 to May 2010, the TOAP was applied to 15 dementia patients and 15 of their caregivers, who was visitors of the Y-city Center for Managing Dementia in Gyunggi-do. The TOAP was designed for habituating patients and caregivers to the techniques acquired through goal activities and task and making it capable of being routinized regularly. The TOAP was applied to dementia patients and their cvaregivers twice a week for 7 weeks(one-time home visit, one-time phone inspection), a total of 14 times. Results: Significant differences among pre-test and post-test were found in the AMPS motor skills(1.10±1.14 and 1.34±1.2 respectively) scores, AMPS process skills(0.32±0.55 and 0.77±0.66 respectively) scores, ACL(3.86±0.65 and 4.17±0.64 respectively) scores, MMSE-KC(17.33±4.6 and 19.33±4.97 respectively) scores, GDS(11.73±6.87 and 8.53±7.09 respectively) scores, and caregiver burden(31.80±20.06 and 26.13±18.07 respectively) scores(p<0.05). A significant effect was confirmed from the TOAP which ADL, cognitive function, reduced patient's depression and caregiver burden(p<0.05). Conclusion: From the above results that a TOAP has an effect on the improvement of the ability to ADL, cognitive function and reduced depression and caregiver burden of dementia patients living in community. The present author hopes that, in the future, more diverse community based on tailored occupational activity programs will be developed to improve the functions of dementia patients living in community.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.370-377
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• 2014

At present trend 3D Printing technology has been using more efficiently than conventional subtractive manufacturing method in various medical fields, in particular this technology superior in saving production time, cost and process than conventional. Especially in orthopedics, an attractive attention has been paid by adopting this technology because of improving operation, operation accuracy, and reducing the patient's pain. Though 3D printing technology has enormous applications still in some hospitals have not been using due to having the problem of technical utilization of hardware, software & chiefly financial availability and etc. In order to solve these problems by reducing the cost and time, we have used CT images in pre-operative planning by directly making the pelvic fracture model with open source DICOM viewer and STL file conversion program, assembly 3D printer of FDM wire additive manufacturing. After having the customized bone model of six patients who underwent unstable pelvic fracture surgery, we have operated our system in orthopedic section of University Hospital through the clinician. Later, we have received better reviews and comments on utilization availability, results, and precision and now our system considered to be useful in surgical planning.

• Progress in Medical Physics
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• v.26 no.3
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• pp.153-159
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• 2015

This study is to evaluate thedosiemtric leaf gap (DLG) at different depths for dynamic intensity-modulated radiation therapy (IMRT) in order to evaluate the absolute dose and dose distribution according to the different positions of tumors and compare the measured and planned the multileaf collimator (MLC) transmission factor (T.F.) and DLG values. We used the 6 MV and 15 MV photon beam from linear accelerator with a Millenium 120 MLC system. After the import the DICOM RT files, we measured the absolute dose at different depths (2 cm, 5 cm, 10 cm, and 15 cm) to calculate the MLC T. F. and DLG. For 6 MV photon beam, the measured both MLC T. F. and DLG were increased with the increase the measured depths. When applying to treatment planning systemas fixed transmission factor with its value measured under the reference condition at depth of 5 cm, although the difference fixed and varied transmission factor is not significant, the dosiemtric effect could be presented according to the depth that the tumor is placed. Therefore, we are planning to investigate the treatment planning system whichthe T. F. and DLG factor according to at the different depths can be applied in the patient-specific treatment plan.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.397-402
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• 2019

Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients' outcomes based on their gene expression data. Gene expression data is high-dimensional numerical data containing about 17,000 genes, so traditional researches used feature selection or dimensionality reduction approaches to elevate the performance of prognostic prediction models. These approaches, however, have an issue of making it difficult for the predictive models to grasp any biological interaction between the selected genes because feature selection and model training stages are performed independently. In this paper, we propose a novel two-dimensional image formatting approach for gene expression data to achieve feature selection and prognostic prediction effectively. Node2Vec is exploited to integrate biological interaction network and gene expression data and a convolutional neural network learns the integrated two-dimensional gene expression image data and predicts cancer prognosis. We evaluated our proposed model through double cross-validation and confirmed superior prognostic prediction accuracy to traditional machine learning models based on raw gene expression data. As our proposed approach is able to improve prediction models without loss of information caused by feature selection steps, we expect this will contribute to development of personalized medicine.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.261-266
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• 2019

Flow cytometry is an electrical detection system that provides precise and diverse optical properties to cells and micro particles. Flow cytometry, which provides multidimensional information including cell size and granularity through light scattering and fluorescence emission generated by the induction of light of a specific wavelength to the fluorescently treated cells or micro particles, plays an important role in biomedical and biophysical fields. However, it has some drawbacks such as high cost, size of the instrument and limitation in selecting fluorescent dyes. Therefore, in this paper, a low cost compact fluorescent detection system is developed using light-emitting diode and microcontroller. The proposed fluorescence detection system has a replaceable the light source/fluorescence filter/photodetector and constructed by 3D printer, so that the user can design a customized system according to the selected fluorescent dyes. The fluorescence intensity was measured by varying the number of fluorescently labeled cells, and the measured intensities showed a high linearity within the tested concentration ranges.