• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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• pp.2935-2937
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• 2014

Studies of the causes of cancer, early detection, prevention or treatment need accurate, comprehensive, and timely cancer data. The clinical laboratory provides important cancer information needed for physicians which influence clinical decisions regarding treatment, diagnosis and patient monitoring. Poor communication between health care providers and clinical laboratory personnel can lead to medical errors and wrong decisions in providing cancer care. Because of the key impact of laboratory information on cancer diagnosis and treatment the quality of the tests, lab reports, and appropriate lab management are very important. A laboratory information management system (LIMS) can have an important role in diagnosis, fast and effective access to cancer data, decrease redundancy and costs, and facilitate the integration and collection of data from different types of instruments and systems. In spite of significant advantages LIMS is limited by factors such as problems in adaption to new instruments that may change existing work processes. Applications of intelligent software simultaneously with existing information systems, in addition to remove these restrictions, have important benefits including adding additional non-laboratory-generated information to the reports, facilitating decision making, and improving quality and productivity of cancer care services. Laboratory systems must have flexibility to change and have the capability to develop and benefit from intelligent devices. Intelligent laboratory information management systems need to benefit from informatics tools and latest technologies like open sources. The aim of this commentary is to survey application, opportunities and necessity of intelligent clinical laboratory as a tool to increase cancer care management productivity.

• Journal of Advanced Marine Engineering and Technology
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• 제30권2호
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• pp.253-259
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• 2006

There is few study which automatically diagnoses the fault from ship's monitored data. The bigger control and monitoring system is. the more important fault diagnosis and maintenance is to reduce damage caused by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault from monitored data and is composed of fault detection knowledge base and fault diagnosis knowledge base. For all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem, To verify capability of fault detection, diagnosis and prediction, FMS(Fault Management System) is developed by C++. Simulation by FMS is carried out with population data set made by the log book data of 2 months duration from a large full container ship of H shipping company.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.251-256
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• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Journal of Preventive Medicine and Public Health
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• 제33권4호
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• pp.393-401
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• 2000

Objectives : To evaluate the impacts of the DRG payment system on the behavior of medical insurance claimants. Specifically, we evaluated the case-mix index, the numbers of diagnosis and procedure codes utilized, and the corresponding rate of diagnosis codes before, during and after implementation of the DRG payment system. Methods : In order to evaluate the case-mix index, the number of diagnosis and procedure codes utilized, we used medical insurance claim data from all medical facilities that participated in the DRG-based Prospective Payment Demonstration Program. This medical insurance claim data consisted of both pre-demonstration program data (fee-for-service, from November, 1998 to January, 1999) and post-demonstration program data (DRG-based Prospective Payment, from February, 1999 to April, 1999). And in order to evaluate the corresponding rate of diagnosis codes utilized, we reviewed 820 medical records from 20 medical institutes that were selected by random sampling methods. Results : The case-mix index rate decreased after the DRG-based Prospective Payment Demonstration Program was introduced. The average numbers of different claim diagnosis codes used decreased (new DRGs from 2.22 to 1.24, and previous DRGs from 1.69 to 1.21), as did the average number of claim procedure codes used (new DRGs from 3.02 to 2.16, and previous DRGs from 2.97 to 2.43). With respect to the time of participation in the program, the change in number of claim procedure codes was significant, but the change in number of claim diagnosis codes was not. The corresponding rate of claim diagnosis codes increased (from 57.5% to 82.6%), as did the exclusion rate of claim diagnosis codes (from 16.5% to 25.1%). Conclusions : After the implementation of the DRG payment system, the corresponding rate of insurance claim codes and the corresponding exclusion rate of claim diagnosis codes both increased, because the inducement system for entering the codes for claim review was changed.

• Design & Manufacturing
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• 제16권4호
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• 한방비만학회지
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• 제9권1호
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• pp.37-44
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• 2009

The study was to investigate the distribution for the diagnosis of pattern identification questionnaire and agreement rate between diagnosis of pattern identification based on obesity pattern identification questionnaire and the clinical diagnosis of pattern' identification by medical specialist. The distribution for the diagnosis of pattern identification based on obesity pattern identification questionnaire was shown in order of stagnation of liver Gi, retention of undigested food, deficiency of Yang at scale of 5, 3, 2 score and the diagnosis rate of single pattern identification at scale of 5, 3, 2 score was 89.96%, 79.33%, 54.64%, respectively the agreement rate between the diagnosis of pattern identification based on obesity pattern identification questionnaire and the clinical diagnosis of pattern identification by medical specialist was 0.1013. Therefore, the complementary management in CRF questionnaires with consultation from experts and the study for score difference of pattern identification will improve the accuracy and agreement rate, which will will be helpful for pattern identification of obesity by clinical experts.

• 한국산학기술학회논문지
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• 제17권1호
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• pp.538-543
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• 2016

고품질의 제품과 조업 안전을 확보하기 위해서는 적절한 실시간 공정 감시 및 진단 시스템이 설치되어있는 것이 무엇보다 중요하다. 공정 감시 시스템과 결합된 신뢰도 높은 진단 시스템은 공정에서 발생한 특별한 사건이나 사고의 근본적인 원인과 공정 변수를 알려준다. 본 연구에서는 다변량 통계 분석과 분류기법에 기반한 공정진단 체계를 제시한다. 이 진단시스템은 비선형 데이터 표현과 필터링을 통한 지능적 데이터 표현으로 구성되어 있다. 진단 성능을 평가하기 위해 사례연구를 수행하였으며 다른 방법론과의 결과를 비교하기 위하여 진단 결과와 미래값 추정 방법을 평가하였다. 그 결과 본 연구에서 비교된 진단 방법론들에 비해 신뢰도 높은 진단 결과를 얻을 수 있었다.

• 한국콘텐츠학회논문지
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• 제17권5호
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• pp.221-233
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• 2017

급변하는 외부 환경에서 생존하기 위해 대부분의 기업은 비즈니스 프로세스를 혁신하거나 개선하고자 노력하고 있으며, 이를 위해 많은 기업들이 프로세스 운영에 BPM (Business Process Management) 개념을 도입하고 있다. 기업에서 BPM 단계는 진단-설계-구현-실행 순으로 진행되는데, BPM 생애 주기에서 통상적으로 비즈니스 프로세스의 진단은 지금까지 주로 인터뷰나 설문지 또는 프로세스를 직접 관찰하는 방식과 같이 수작업으로 이루어졌다. 비즈니스 프로세스의 (재)설계 방법도 주로 백지 상태에서 시작하여 전문가의 지식에 의존하는 수작업 방식으로 이루어져 왔다. 이 연구의 목적은 프로세스 진단 단계에서 프로세스 마이닝을 이용하여 자동으로 생성된 프로세스 모델과 통계량을 (재)설계 단계에서도 공유함으로써 별개로 행해지던 진단과 설계 업무를 통합하려는 것이다. 이러한 시도의 궁극적인 목표는 비즈니스 프로세스 진단과 설계 업무를 자동화하려는 것이다. 제안 프레임워크를 구현하고 유용성을 제시하기 위해 두 개의 사례 연구를 행하였다.

• Journal of Animal Science and Technology
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• 제65권2호
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• pp.365-376
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• 2023

Pig breeding management directly contributes to the profitability of pig farms, and pregnancy diagnosis is an important factor in breeding management. Therefore, the need to diagnose pregnancy in sows is emphasized, and various studies have been conducted in this area. We propose a computer-aided diagnosis system to assist livestock farmers to diagnose sow pregnancy through ultrasound. Methods for diagnosing pregnancy in sows through ultrasound include the Doppler method, which measures the heart rate and pulse status, and the echo method, which diagnoses by amplitude depth technique. We propose a method that uses deep learning algorithms on ultrasonography, which is part of the echo method. As deep learning-based classification algorithms, Inception-v4, Xception, and EfficientNetV2 were used and compared to find the optimal algorithm for pregnancy diagnosis in sows. Gaussian and speckle noises were added to the ultrasound images according to the characteristics of the ultrasonography, which is easily affected by noise from the surrounding environments. Both the original and noise added ultrasound images of sows were tested together to determine the suitability of the proposed method on farms. The pregnancy diagnosis performance on the original ultrasound images achieved 0.99 in accuracy in the highest case and on the ultrasound images with noises, the performance achieved 0.98 in accuracy. The diagnosis performance achieved 0.96 in accuracy even when the intensity of noise was strong, proving its robustness against noise.

• 벤처창업연구
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• 제3권1호
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• pp.57-72
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• 2008

본 논문에서는 그동안 부분적으로 진행된 발달장애 진단 평가에 관련된 전산처리를 멀티미디어 기법을 응용하여 발달장애 진단 평가분야에 새로운 방법을 제시한다. 발달장애 진단 평가를 위한 멀티미디어 정보는 여러 가지 속성을 지니고 있기 때문에 모든 발달장애 진단 평가 정보에 대한 기술을 사람이 수행해야 할 때는 엄청난 작업량이 수반될 뿐 아니라 동일한 데이터에 대한 기술이 주관에 따라 달라질 수도 있다는 것을 알게 되였다. 특히 발달장애 시스템 구현은 현재의 컴퓨팅 환경에서의 동영상 데이터 처리에 대한 비중의 증가, 텍스트 위주의 데이터에서 시각적인 동영상으로의 데이터 활용의 전이 등 발달장애 데이터가 멀티미디어 환경에 적합한 데이터로의 전이가 필수적이며 사용자 역시 빠른 이해를 위해 시각적 데이터를 선호하기 때문에 본 논문에서는 GUI(Graphics User Interface) 기법을 도입하여 검사 중에 텍스트 명령어는 거의 사용하지 않고도 발달장애 진단 평가를 수행할 수 있게 했다. 특히 발달장애 진단 평가에서 필요한 각종 데이터는 그 속성이 영상, 이미지, 논리연산의 필요성 및 각종 연산이 요구된다. 그래서 본 논문에서는 문제점을 해결하기 위해 편집대상 데이터(Content)에 의해 관련 정보를 검색하는 내용 기반(Content-based)의 검색 기술에 대한 연구를 적용했다.