• Title/Summary/Keyword: 의료 모델

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Systematic Review on Outcome and Trends of Community Care Pilot Project in Korea (국내 지역사회 통합돌봄 선도사업 성과 및 동향에 관한 체계적 문헌고찰)

  • Kim, Kyoung-Beom;Heo, Min-Hee;Jang, Ha-Eun;Noh, Jin-Won;Kim, Jang-Mook
    • Journal of Convergence for Information Technology
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    • v.12 no.5
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    • pp.159-167
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    • 2022
  • At the present time, no systematic review has been conducted to report the project's outcomes or trends. This study systematically reviewed existing evidence related with community care pilot project. A total of 61 articles, including 18 original literatures and 43 review literatures were finally selected. For original literatures, the most frequent literatures focused on demand surveys (n=4) and model proposals (n=4), the utilization of touchpoint (n=3), space design and architectural model (n=3), manpower training and role establishment (n=2), followed by prioritizing objectives (n=1) and research trend study (n=1). For review literatures, the most frequent literature focused on the elderly (n=12) and relatively few literature on the disabled and mental illness (n=2). Since the pilot project for community care has been implemented for only about one year, the present study indicates that more future research is needed to the disabled, mental illness, and homeless should be conducted as well as elderly.

Corneal Ulcer Region Detection With Semantic Segmentation Using Deep Learning

  • Im, Jinhyuk;Kim, Daewon
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.9
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    • pp.1-12
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    • 2022
  • Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

A Study on Factors Affecting a User's Behavioral Intention to Use Cloud Service for Each Industry (클라우드 서비스의 산업별 이용의도에 미치는 영향요인에 관한 연구)

  • Kwang-Kyu Seo
    • Journal of Service Research and Studies
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    • v.10 no.4
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    • pp.57-70
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    • 2020
  • Globally, cloud service is a core infrastructure that improves industrial productivity and accelerates innovation through convergence and integration with various industries, and it is expected to continuously expand the market size and spread to all industries. In particular, due to the global pandemic caused by COVID-19, the introduction of cloud services was an opportunity to be recognized as a core infrastructure to cope with the untact era. However, it is still at the preliminary stage for market expansion of cloud service in Korea. This paper aims to empirically analyze how cloud services can be accepted by users by each industry through extended Technology Acceptance Model(TAM), and what factors influence the acceptance and avoidance of cloud services to users. For this purpose, the impact and factors on the acceptance intention of cloud services were analyzed through the hypothesis test through the proposed extended technology acceptance model. The industrial sector selected four industrial sectors of education, finance, manufacturing and health care and derived factors by examining the parameters of TAM, key characteristics of the cloud and other factors. As a result of the empirical analysis, differences were found in the factors that influence the intention to accept cloud services for each of the four industry sectors, which means that there is a difference in perception of the introduction or use of cloud services by industry sector. Eventually it is expected that this study will not only help to understand the intention of using cloud services by industry, but also help cloud service providers expand and provide cloud services to each industry.

Dental Surgery Simulation Using Haptic Feedback Device (햅틱 피드백 장치를 이용한 치과 수술 시뮬레이션)

  • Yoon Sang Yeun;Sung Su Kyung;Shin Byeong Seok
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.6
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    • pp.275-284
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    • 2023
  • Virtual reality simulations are used for education and training in various fields, and are especially widely used in the medical field recently. The education/training simulator consists of tactile/force feedback generation and image/sound output hardware that provides a sense similar to a doctor's treatment of a real patient using real surgical tools, and software that produces realistic images and tactile feedback. Existing simulators are complicated and expensive because they have to use various types of hardware to simulate various surgical instruments used during surgery. In this paper, we propose a dental surgical simulation system using a force feedback device and a morphable haptic controller. Haptic hardware determines whether the surgical tool collides with the surgical site and provides a sense of resistance and vibration. In particular, haptic controllers that can be deformed, such as length changes and bending, can express various senses felt depending on the shape of various surgical tools. When the user manipulates the haptic feedback device, events such as movement of the haptic feedback device or button clicks are delivered to the simulation system, resulting in interaction between dental surgical tools and oral internal models, and thus haptic feedback is delivered to the haptic feedback device. Using these basic techniques, we provide a realistic training experience of impacted wisdom tooth extraction surgery, a representative dental surgery technique, in a virtual environment represented by sophisticated three-dimensional models.

A Simulation Study for Improving Operations of an Emergency Medical Center (응급진료센터 운영 개선을 위한 시뮬레이션)

  • Mo, Chang-Woo;Choi, Seong-Hoon
    • Journal of the Korea Society for Simulation
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    • v.18 no.3
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    • pp.35-45
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    • 2009
  • Emergency medical center(EMC) is the place for patients who need medical treatment immediately due to a disease, childbirth, or all sorts of accidents. Currently, most of EMCs use temporary beds because regular EMC beds cannot afford to serve all incoming patients. However, since it decreases the quality of service(QoS) of EMC patients and their guardians and efficiency of the EMC, some improvements are highly required to diminish the usage of temporary beds. The system duration time is one of the typical QoSs. This thesis proposes the information which is critical to make a better decision for cut down the number of temporary beds without sacrificing QoS of patients. The key point is to control the duration time of medical treatments for the consultation and hospitalization process, since it is the major reason of overcrowding in EMC and the usage of temporary beds. In this paper, we proposed an Arena simulation model reflecting real world substantially. Arena is one of the most widely accepted simulation softwares in the world. Using the developed model, we can obtain the optimal EMC operation parameters through simulation experiments. Optquest, included in the Arena, is used to make the developed simulation model collaborate with an optimization model. The results showed one can determine the set of optimal operation parameters decreasing the required number of temporary beds without deteriorating EMC patient's QoS.

Meta-analysis of the Interventions for Caring Depression of the Elderly in the Four Countries: A Comparison of the Total Effectiveness, Short-term Effectiveness, and Long-term Effectiveness (노인 우울증 관리 프로그램의 효과성 메타 분석: 전체·단기·장기 효과성의 비교)

  • Park, Seung-Min
    • 한국노년학
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    • v.31 no.3
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    • pp.553-571
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    • 2011
  • The purpose of this research is to comparatively meta-analyze the total, short-term, and long-termeffectiveness of cases involving care of the elderly depression in the age range of 60 and over in the four countries, and to identify the relevant policy implications for developing depression care programmes for Korean older people. Ten studies conducted by RCT were found via AMED, EMBASE, Ovid Medline, PsycInfo. Use of Review Manager(5.5 version) shows that the interventions for caring depression were all effective: total effectiveness is OR=0.47(95% CI), short-termeffectiveness is OR=0.37(95% CI), and long-term effectiveness is OR=0.61(95% CI). This research provides three policy implications: Firstly, elements for increasing the long-term effectiveness of depression care interventions should be applied to all new programmes for caring elderly depression. Secondly, more focused depression interventions should be applied during the first half period of care programmes for elderly men, whilst the focus should be shifted to the last half period for elderly women. Finally, new interventions for caring depression that integrate both the medical and social support model of depression should be designed for elderly Koreans.

Domain-Specific Terminology Mapping Methodology Using Supervised Autoencoders (지도학습 오토인코더를 이용한 전문어의 범용어 공간 매핑 방법론)

  • Byung Ho Yoon;Junwoo Kim;Namgyu Kim
    • Information Systems Review
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    • v.25 no.1
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    • pp.93-110
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    • 2023
  • Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.

Three-Dimensional Printed Model of Partial Anomalous Pulmonary Venous Return with Biatrial Connection (양측 심방 연결을 형성하는 부분 폐정맥 환류 이상의 3D 프린팅 모델)

  • Myoung Kyoung Kim;Sung Mok Kim;Eun Kyoung Kim;Sung-A Chang;Tae-Gook Jun;Yeon Hyeon Choe
    • Journal of the Korean Society of Radiology
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    • v.81 no.6
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    • pp.1523-1528
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    • 2020
  • Partial anomalous pulmonary venous return (PAPVR) is a rare congenital cardiac anomaly that can be difficult to detect and often remains undiagnosed. PAPVR is diagnosed using non-invasive imaging techniques such as echocardiography, CT, and MRI. Image data are reviewed on a 2-dimensional (D) monitor, which may not facilitate a good understanding of the complex 3D heart structure. In recent years, 3D printing technology, which allows the creation of physical cardiac models using source image datasets obtained from cardiac CT or MRI, has been increasingly used in the medical field. We report a case involving a 3D-printed model of PAPVR with a biatrial connection. This model demonstrated separate drainages of the right upper and middle pulmonary veins into the lower superior vena cava (SVC) and the junction between the SVC and the right atrium, respectively, with biatrial communication through the right middle pulmonary vein.

A Study on an Automatic Classification Model for Facet-Based Multidimensional Analysis of Civil Complaints (패싯 기반 민원 다차원 분석을 위한 자동 분류 모델)

  • Na Rang Kim
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.1
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    • pp.135-144
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    • 2024
  • In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

Birth Weight Distribution by Gestational Age in Korean Population : Using Finite Mixture Modle (우리나라 신생아의 재태 연령에 따른 출생체중의 정상치 : Finite Mixture Model을 이용하여)

  • Lee, Jung-Ju;Park, Chang Gi;Lee, Kwang-Sun
    • Clinical and Experimental Pediatrics
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    • v.48 no.11
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    • pp.1179-1186
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    • 2005
  • Purpose : A universal standard of the birth weight for gestational age cannot be made since girth weight distribution varies with race and other sociodemographic factors. This report aims to establish the birth weight distribution curve by gestational age, specific for Korean live births. Methods : We used the national birth certificate data of all live births in Korea from January 2001 to December 2003; for live births with gestational ages 24 weeks to 44 weeks(n=1,509,763), we obtained mean birth weigh, standard deviation and 10th, 25th, 50th, 75th and 90th percentile values for each gestational age group by one week increment. Then, we investigated the birth weight distribution of each gestational age group by the normal Gaussian model. To establish final standard values of Korean birth weight distribution by gestational age, we used the finite mixture model to eliminate erroneous birth slights for respective gestational ages. Results : For gestational ages 28 weeks 32 weeks, birth weight distribution showed a biologically implausible skewed tail or bimodal distribution. Following correction of the erroneous distribution by using the finite mixture model, the constructed curve of birth weight distribution was compared to those of other studies. The Korean birth weight percentile values were generally lower than those for Norwegians and North Americans, particularly after 37 weeks of gestation. The Korean curve was similar to that of Lubchenco both 50th and 90th percentiles, but generally the Korean curve had higher 10th percentile values. Conclusion : This birth weight distribution curve by gestational age is based on the most recent and the national population data compared to previous studies in Korea. We hope that for Korean infants, this curve will help clinicians in defining and managing the large for gestational age infants and also for infants with intrauterine growth retardation.