• Asian Pacific Journal of Cancer Prevention
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• 제14권3호
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• pp.2013-2017
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• 2013

Background: To compare the effects of two adjuvant chemotherapy regimens, anthracycline-based and cyclophosphamide, methotrexate, fluorourical (CMF) on disease free survival for breast cancer patients in the Eastern Mediterranean region and Asia. Methods: In a systematic review with a multivariate mixed model meta-analysis, the reported survival proportion at multiple time points in different studies were combined. Our data sources were studies linking the two chemotherapy regimens on an adjuvant basis with disease free survival published in English and Persian in the Eastern Mediterranean region and Asia. All survival curves were generated with Graphdigitizer software. Results: 14 retrospective cohort studies were located from electronic databases. We analyzed data for 1,086 patients who received anthracycline-based treatment and 1,109 given CMF treatment. For determination of survival proportions and time we usesb the transformation Ln (-Ln(S)) and Ln (time) to make precise estimations and then fit the model. All analyses were carried out with STATA software. Conclusions: Our findings showed a significant efficacy of anthracycline-based adjuvant therapy regarding disease free survival of breast cancer. As a limitation in this meta-analysis we used studies with different types of anthracycline-based regimens.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.974-992
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• 2021

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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• pp.1634-1652
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• 2022

Due to the increasing need for data sharing in the age of big data, how to achieve data access control and implement user permission revocation in the blockchain environment becomes an urgent problem. To solve the above problems, we propose a novel blockchain-based data sharing scheme (BDSS) with fine-grained access control and permission revocation in this paper, which regards the medical environment as the application scenario. In this scheme, we separate the public part and private part of the electronic medical record (EMR). Then, we use symmetric searchable encryption (SSE) technology to encrypt these two parts separately, and use attribute-based encryption (ABE) technology to encrypt symmetric keys which used in SSE technology separately. This guarantees better fine-grained access control and makes patients to share data at ease. In addition, we design a mechanism for EMR permission grant and revocation so that hospital can verify attribute set to determine whether to grant and revoke access permission through blockchain, so it is no longer necessary for ciphertext re-encryption and key update. Finally, security analysis, security proof and performance evaluation demonstrate that the proposed scheme is safe and effective in practical applications.

• Asian Pacific Journal of Cancer Prevention
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• 제15권17호
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• pp.7449-7452
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• 2014

Background: The purpose of this study was to investigate the correlation of contrast-enhanced ultrasonographic (CEUS) features with microvessel density (MVD) in papillary thyroid carcinomas (PTCs). Materials and Methods: Contrast-enhanced ultrasonography (CEUS) was performed in 62 patients (17 men and 45 women) with PTC. Tomtec software was applied to analyze the time intensity curve of CEUS. Immunohistochemistry was performed to evaluate the level of MVD in papillary thyroid carcinoma. Then the relationship between quantitative feature and the level of MVD was analyzed using SPSS 16.0 software. Results: The mean peak intensity of PTC tissues was lower than that of peripheral thyroid parenchyma ($61.9{\pm}11.8%$ vs 100%, p<0.05). The MVDs of CD34 and CD31 antibodies staining were $38.0{\pm}6.1$ and $37.9{\pm}5.1$ respectively in 62 PTC samples. A significantly positive correlation was observed between peak intensity and MVD in PTC tissues ($P_{CD34}$<0.01, $r_{CD34}$=0.838, $P_{CD31}$<0.01, $r_{CD31}$=0.837). Conclusions: The peak intensity in CEUS could reflect the MVD in PTC tissues. Therefore, quantification of CEUS seems to be helpful for assessment of MVD in PTC tissues.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.104-107
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• 1997

A medical teleconferencing and medical image transmision system has been developed for diagnosis of the medical images between the medical doctors who are far away. The medical teleconferencing system transmits the voice and image of the doctors using the video and audio capture boards. The medical image transmission system software uses the medical image standard DICOM 3.0 for the future expansibility and the open system interconectivity. The medical images usually use CR images.

• Journal of Information Processing Systems
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• 제13권6호
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• pp.1602-1612
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• 2017

Since rapidly disseminating of Internet of Things (IoT) as the new communication paradigm, a number of studies for various applications is being carried out. Especially, interest in the smart medical system is rising. In the smart medical system, a number of medical devices are distributed in popular area such as station and medical center, and this high density of medical device distribution can cause serious performance degradation of communication, referred to as the coexistence problem. When coexistence problem occurs in smart medical system, reliable transmitting of patient's biological information may not be guaranteed and patient's life can be jeopardized. Therefore, coexistence problem in smart medical system should be resolved. In this paper, we propose a distributed coexistence mitigation scheme for IoT-based smart medical system which can dynamically avoid interference in coexistence situation and can guarantee reliable communication. To evaluate the performance of the proposed scheme, we perform extensive simulations by comparing with IEEE 802.15.4 MAC protocol which is a traditional low-power communication technology.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• 한국IT서비스학회지
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• 제11권4호
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• pp.295-308
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• 2012

Software and Systems Product Line(SSPL) is a paradigm that has been developed and applied by European Union(EU) to achieve the productivity and competitiveness of EU industries on the world market. It is not just a simple system or software development methodology, but a sophisticated technology requiring capabilities for a high level of mass customization, platforms, processes and convergence of software and systems. EU has applied SSPL for the five selected industrial sectors including aerospace, automobile, medical equipment, consumer electronics and telecommunication equipment since 1990s and led the way to other industry sectors to stimulate the application of SSPL from 2006. In order for Korea to secure competitiveness in the manufacturing and service industries in the competitive borderless market, it is essential to gain the high level of capabilities for software development and convergence of software and systems. SSPL can be a powerful means to achieve this end. This paper discusses the paradigmatic concept of SSPL, how EU's major industries and companies have secured competitiveness through SSPL, key capabilities that are necessary for successful institutionalization of SSPL in Korea, and finally suggestions on core strategies to materialize the benefits of SSPL for Korea.

• 한국전자파학회논문지
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• 제27권2호
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• pp.216-219
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• 2016

본 논문에서는 SIW(Substrate Integrated Waveguide) 구조를 갖는 SDR(Software Defined Radar)용 안테나를 설계하고 제작하였다. SIW 구조는 쉬운 집적화로 인하여 일반 PCB 상에 구현이 가능하고, 기존의 구형 도파관과 같이 높은 전력의 입력 신호에 대하여 낮은 전송손실을 가지는 특성이 있다. 또한, 전자기 간섭에 대하여 강한 내성을 갖는 장점이 있다. 특히 본 논문에서는 제작한 SIW 안테나를 가지고 USRP(Universal Software Radio Peripheral) 플랫폼에 탑재하여 목표물 RCS(Radar Cross Section)탐지 실험을 진행하였다. 제안된 안테나는 ISM(Industrial, Scientific and Medical) 대역(2.4~2.48 GHz)에서 동작하며, 이득 특성은 8 dBi 이상을 보인다.

• 한국의학물리학회지:의학물리
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• 제33권4호
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• pp.136-141
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• 2022

Purpose: This study aimed to develop a breath control training system for breath-hold technique and respiratory-gated radiation therapy wherein the patients can learn breath-hold techniques in their convenient environment. Methods: The breath control training system comprises a sensor device and software. The sensor device uses a loadcell sensor and an adjustable strap around the chest to acquire respiratory signals. The device connects via Bluetooth to a computer where the software is installed. The software visualizes the respiratory signal in near real-time with a graph. The developed system can signal patients through visual (software), auditory (buzzer), and tactile (vibrator) stimulation when breath-holding starts. A motion phantom was used to test the basic functions of the developed breath control training system. The relative standard deviation of the maxima of the emulated free breathing data was calculated. Moreover, a relative standard deviation of a breath-holding region was calculated for the simulated breath-holding data. Results: The average force of the maxima was 487.71 N, and the relative standard deviation was 4.8%, while the average force of the breath hold region was 398.5 N, and the relative standard deviation was 1.8%. The data acquired through the sensor was consistent with the motion created by the motion phantom. Conclusions: We have developed a breath control training system comprising a sensor device and software that allow patients to learn breath-hold techniques in their convenient environment.