• Title/Summary/Keyword: Healthcare information systems

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A Study on account and authority management method of IOT system (IOT 체계의 계정 및 권한관리 방법에 대한 연구)

  • Kim, Min-Hwi;Kim, Young-kil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.225-228
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    • 2017
  • In this paper, we propose a methodology to deal with the IOT system gradually as the use of effective systems such as electronic devices, healthcare, smart cars, smart home, remote meter reading and telemedicine closely related to our real life in the IOT system An IOT integrated account solution is needed as a way to address these needs as the demand grows for the need to identify and manage how users access and use the system for what period of time and at what point in time. We propose the communication algorithms for endpoint system, IOT system management rights policy, user information, and how to apply them to IOT system smart car and smart home on each object internet.

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Data Mining for Knowledge Management in a Health Insurance Domain

  • Chae, Young-Moon;Ho, Seung-Hee;Cho, Kyoung-Won;Lee, Dong-Ha;Ji, Sun-Ha
    • Journal of Intelligence and Information Systems
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    • v.6 no.1
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    • pp.73-82
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    • 2000
  • This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

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Enhanced 3D Residual Network for Human Fall Detection in Video Surveillance

  • Li, Suyuan;Song, Xin;Cao, Jing;Xu, Siyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.12
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    • pp.3991-4007
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    • 2022
  • In the public healthcare, a computational system that can automatically and efficiently detect and classify falls from a video sequence has significant potential. With the advancement of deep learning, which can extract temporal and spatial information, has become more widespread. However, traditional 3D CNNs that usually adopt shallow networks cannot obtain higher recognition accuracy than deeper networks. Additionally, some experiences of neural network show that the problem of gradient explosions occurs with increasing the network layers. As a result, an enhanced three-dimensional ResNet-based method for fall detection (3D-ERes-FD) is proposed to directly extract spatio-temporal features to address these issues. In our method, a 50-layer 3D residual network is used to deepen the network for improving fall recognition accuracy. Furthermore, enhanced residual units with four convolutional layers are developed to efficiently reduce the number of parameters and increase the depth of the network. According to the experimental results, the proposed method outperformed several state-of-the-art methods.

Development of Abnormal Situation Managenet System in Process-centric Way for Enhancing Patient Safety (환자 안전 제고를 위한 프로세스 중심적인 이상상황 관리 시스템 개발)

  • Moon, Junho;Kim, Dongsoo
    • Journal of Information Technology and Architecture
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    • v.11 no.1
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    • pp.89-97
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    • 2014
  • As ubiquitous computing technologies have advanced rapidly, context awareness technology has been used in the medical part in order to improve patient safety. Nevertheless, as there is no method for managing context awareness information effectively and managing healthcare processes for handling abnormal situations systematically, it is highly required to enhance patient safety in hospital. We propose an innovative system to solve these problems. The proposed system has three main functionalities. Firstly, it enables all situations to be recognized in medical organizations. Secondly, it extracts the meaningful data from data flood by defining data patterns of recognized situations and designing a rule-based system. Lastly, it can manage patients' abnormal situations in process-centric way by integrating the business process management system. It is expected that the proposed system contributes to the improvement of patient safety in u-hospital.

Artificial Intelligence based Tumor detection System using Computational Pathology

  • Naeem, Tayyaba;Qamar, Shamweel;Park, Peom
    • Journal of the Korean Society of Systems Engineering
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    • v.15 no.2
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    • pp.72-78
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    • 2019
  • Pathology is the motor that drives healthcare to understand diseases. The way pathologists diagnose diseases, which involves manual observation of images under a microscope has been used for the last 150 years, it's time to change. This paper is specifically based on tumor detection using deep learning techniques. Pathologist examine the specimen slides from the specific portion of body (e-g liver, breast, prostate region) and then examine it under the microscope to identify the effected cells among all the normal cells. This process is time consuming and not sufficiently accurate. So, there is a need of a system that can detect tumor automatically in less time. Solution to this problem is computational pathology: an approach to examine tissue data obtained through whole slide imaging using modern image analysis algorithms and to analyze clinically relevant information from these data. Artificial Intelligence models like machine learning and deep learning are used at the molecular levels to generate diagnostic inferences and predictions; and presents this clinically actionable knowledge to pathologist through dynamic and integrated reports. Which enables physicians, laboratory personnel, and other health care system to make the best possible medical decisions. I will discuss the techniques for the automated tumor detection system within the new discipline of computational pathology, which will be useful for the future practice of pathology and, more broadly, medical practice in general.

A Security Reference Model for the Construction of Mobile Banking Services based on Smart Phones

  • Shin, Yong-Nyuo;Shin, Woo-Chang
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.4
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    • pp.229-237
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    • 2011
  • As smart phones have become widely adopted, they have brought about changes in individual lifestyles, as well as significant changes in the industry. As the mobile technology of smart phones has become associated with all areas of industry, it is not only accelerating innovation in other industries such as shopping, healthcare service, education, and finance, but is also creating new markets and business opportunities. The preparation of thorough security measures for smart phones is increasing in demand. While offering excellent mobility and convenience, smart phones can be exposed to a range of violation threats. In particular, it is necessary to make efforts to develop a security system that can preemptively cope with potential security threats in the banking service area, which requires a high level of reliability. This paper suggests a security reference model that is considered for the smart phone-based joint mobile banking development project being undertaken by the Bank of Korea in 2010. The purpose of this study is to make a security reference model for a reliable smart phone-based mobile financial service, by recognizing the specific security threats directed toward smart phones, and providing countermeasures to these security threats. The proposed mobile banking security reference model is useful in improving system security by systematically analyzing information security threats to the mobile financial service, and by presenting the guideline for the preparation of countermeasures.

Real-time 3-Dimensional Measurement of Lumbar Spine Range of Motion using a Wireless Sensor (무선 센서를 활용한 요추 가동 범위의 실시간 3차원 측정)

  • Jeong, Woo-Hyuk;Jee, Hae-Mi;Park, Jae-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.8
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    • pp.713-718
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    • 2012
  • Lumber spine range of motion has been used to measure of physical and functional impairment by various tools from a ruler to 3D kinematic devices. However, pre-existing tools have problems in either movement or accuracy and reliability limitations. Accurate devices are limited by fixed space whereas simple devices are limited in measuring complex movements with less accuracy. In order to solve the location, movement and accuracy limitations at once, we have developed a novice measurement device equipped with accelerometer sensor and gyroscope sensor for getting three-dimensional information of motion. Furthermore, Kalman filter was applied to the algorithm to improve accuracy. In addition, RF wireless communication was added for the user to conveniently check measured data in real time. Finally, the measurement method was improved by considering the movement by a reference point. An experiment was conducted to test the accuracy and reliability of the device by conducting a test-retest reliability test. Further modification will be conducted to used the device in various joints range of motion in clinical settings in the future.

Patent analysis and Creation of new core patents for ERP-based real-time data archiving (ERP 기반 실시간 데이터 아카이빙 기술에 관한 특허 분석 및 신규 핵심특허 창출에 관한 연구)

  • Gayun Kim;Sehun Jung;Jinhong Yang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.2
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    • pp.99-107
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    • 2024
  • The recent digital transformation in many industries has led to an explosion of data, which has exponentially increased the amount of data that companies need to generate and process. As a result, enterprises are leveraging ERP systems to manage and analyze large amounts of data in real time. However, due to cost and time issues in processing large amounts of data in existing ERP systems, it is essential to apply data archiving technology that can compress and store data in real time in existing systems. Therefore, this paper aims to identify the trends of the target technology by utilizing patent data on ERP-based real-time data archiving technology, analyze the core patents, and create new core patents based on them.

Changes in the Behavior of Healthcare Organizations Following the Introduction of Drug Utilization Review Evaluation Indicators in the Healthcare Quality Evaluation Grant Initiative (의료질평가지원금 제도의 의약품안전사용서비스 평가지표 도입에 따른 의료기관의 행태 변화)

  • Hyeon-Jeong Kim;Ki-Bong Yoo;Young-Joo Won;Han-Sol Jang;Kwang-Soo Lee
    • Health Policy and Management
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    • v.34 no.2
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    • pp.178-184
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    • 2024
  • Background: This study aimed to determine the effectiveness of drug utilization review (DUR) evaluation indicators on safe drug use by comparing the changes in DUR inspection rates and drug duplication prescription prevention rates between the pre- and post-implementation of the DUR evaluation indicators of the Healthcare Quality Evaluation Grant Initiative. Methods: This study used DUR data from the Health Insurance Review and Assessment Service in 2018 (pre-implementation) and the evaluation results of the Healthcare Quality Evaluation Grant Initiative in 2023 (post-implementation). The dependent variables were the DUR evaluation indicators, including DUR inspection rate and drug duplicate prescription prevention rate. The independent variable was the implementation of the DUR evaluation indicators, and the control variables included medical institution characteristics such as type, establishment classification, location, DUR billing software company, and number of beds. Results: The results of the analysis of the difference in the prevention rate of drug duplicate prescriptions between the pre- and post-implementation of the DUR evaluation indicators of the Healthcare Quality Evaluation Grant Initiative showed that the prevention rate of drug duplicate prescriptions increased statistically significantly after the implementation of the DUR evaluation indicators. Conclusion: The policy implications of this study are as follows: First, ongoing evaluation of DUR systems is needed. Second, it is necessary to establish a collaborative partnership between healthcare organizations that utilize DUR system information and the organizations that manage it.

Medical Information Privacy Concerns in the Use of the EHR System: A Grounded Theory Approach (의료정보 프라이버시 염려에 대한 근거이론적 연구: 전자건강기록(EHR) 시스템을 중심으로)

  • Eom, Doyoung;Lee, Heejin;Zoo, Hanah
    • Journal of Digital Convergence
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    • v.16 no.1
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    • pp.217-229
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    • 2018
  • Electronic Health Record (EHR) systems are widely adopted worldwide in hospitals for generating and exchanging records of patient information. Recent developments are moving towards implementing interoperable EHR systems that enable information to be shared seamlessly across healthcare organizations. In this context, this paper explores the factors that cause medical information privacy concerns, identifies how people react to privacy invasion and what their perceptions are towards the acceptance of the EHR system. Interviews were conducted to draw a grounded theory on medical information privacy concerns in the use of EHRs. Medical information privacy concerns are caused by perceived sensitivity of medical information and the weaknesses in security technologies. Trust in medical professionals, medical institutions and technologies plays an important role in determining people's reaction to privacy invasion and their perceptions on the use of EHRs.