• 디지털융복합연구
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• 제15권8호
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• pp.289-299
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• 2017

본 연구는 만성 통증이 있는 노인의 통증, 수면, 우울이 삶의 질에 미치는 영향을 알아보기 위해 수행되었다. 지역사회 65세 이상 노인 170명을 대상으로 2016년 7월 1일부터 9월 30일까지 수집된 자료를 다중 회귀 분석으로 분석하였다. 그 결과, 만성 통증 노인의 통증, 수면, 우울, 삶의 질은 일반적인 특성 중 성별, 나이, 생활 상태, 교육 수준, 경제적 상태, 주관적 건강 상태 및 우울증 치료 여부에 따른 유의적 차이가 나타났으며, 통증 관련 특성 중에서는 통증 정도, 통증 지속기간, 통증 시간에 따른 유의적인 차이가 있었다. 또한, 만성통증 노인의 삶의 질과 삶의 질 세부항목은 수면(.471, p<.001)과 양의 상관관계가, 통증(-.332, p<.001), 우울(-.720, p<.001)과는 음의 상관관계가 있는 것으로 나타났다. 본 연구에서 만성통증 노인의 삶의 질에 유의미한 영향을 주는 요인은 주관적 건강 상태(${\beta}=.236$, p=.001), 우울증 진단 여부(${\beta}=.123$, p=.048), 우울(${\beta}=-.526$, p<.001)이었으며, 우울 관련 요인이 가장 영향력이 높았다. 따라서 만성 통증을 가진 노인들의 삶의 질을 향상시키기 위해서는 우울증과 통증을 줄이기 위한 간호 및 관리 프로그램을 마련해야 할 것이다.

• 디지털융복합연구
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• 제18권1호
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• pp.257-263
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• 2020

본 연구는 건강보험심사평가원 자료를 이용하여 조현병 환자의 인구사회학적 특성, 의료기관 특성, 입퇴원 특성이 재원일수에 미치는 영향을 분석하여 국가 보건 정책 질 향상을 위한 기초 자료로 활용하고자 시행하였다. 건강보험심사평가원 2016년 환자 데이터셋(HIRA-NIS)에서 조현병이 주진단인 4,692명의 진료비 명세서를 연구대상으로 하였다. 조현병 환자의 재원일수 영향 요인을 확인하기 위하여 인구사회학적 특성, 의료기관 특성, 입퇴원 특성을 설명변수로, 재원일수를 종속변수로 회귀분석을 실시하였다. 연구결과 재원일수에 주요하게 영향을 미치는 요인은 여자, 연령, 의료 급여, 병원급, 요양병원, 강원도, 정신질환 부진단, 기타 부진단 등으로 밝혀졌다. 공공 데이터를 이용하여 조현병 환자의 재원일수에 영향을 미치는 요인을 찾고자 함에 의의가 있으며, 중증도는 고려하고 있지 않아 향후 중증도에 따른 재원일수의 차이에 대한 연구가 진행되어야 할 것으로 보여 진다.

• 방송공학회논문지
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• 제25권1호
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• pp.13-24
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• 2020

한국에는 전력 분배를 위하여 약 9백만 개의 전신주와 1.3백만 킬로미터의 송전선이 있다. 이러한 많은 전력 설비의 유지보수를 위해서는 많은 인력과 시간이 소요된다. 최근 인공지능을 사용한 여러 고장진단 기술들이 연구되어 오고 있기 때문에 본 논문에서는 송전선의 여러 요인으로 인한 늘어짐을 감지하기 위해 기존의 현장에서의 검증 방법이 아닌 카메라 시스템으로 촬영한 영상에서의 인공 지능 기술을 활용한 송전선 늘어짐 감지 시스템을 제안한다. 제안하는 시스템은 (i) 객체 탐지 시스템을 이용한 송전탑 감지 (ii) 동영상 촬영 데이터의 화질 저하 문제를 해결하기 위한 히스토그램 평활화 기법 (iii) 송전선 전체를 파악하기 위한 파노라마 영상 스티칭(iv) 송전선 탐지 알고리즘 적용 후 파노라마 영상 스티칭 기술을 이용한 늘어짐 판단 과정으로 진행된다. 본 논문에서는 각각의 과정들에 대한 설명 및 실험 결과를 보인다.

• Journal of Acupuncture Research
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• 제22권2호
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• pp.163-170
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• 2005

Background : Over the last thirty years, majority of researches on clinical effectiveness of acupuncture have been explanatory (or experimental) randomized controlled trial. The benefits of acupuncture in clinical trials are still controversial and most studies concluded that further control studies were required. Standardized combinations of acupuncture points for all the experimental subjects in various past studies have been criticized because such treatments do not reflect current routine clinical treatment. Objective : This paper aims to review pragmatic clinical trials on the effect of acupuncture treatment and to develop the ideal clinical research methodology of acupuncture study. Method : Clinical studies of acupuncture relevant with pragmatic or individualized trials were searched mainly in Pubmed and Science direct databases. All articles were fully reviewed by researchers, and data were evaluated by usage of a standardized form. Results & Suggestion : Pragmatic acupuncture researches were tried for various symptoms (eg. low back pain, hypertension, depression during pregnancy, sleep quality in HIV disease, chronic poststroke leg spasticity, headache, etc). Individualized acupuncture treatments based on oriental disease pattern diagnosis reflexes practical treatments which is more effective than unified and fixed acupuncture treatments without any theoretical basis of oriental medical philosophy. Conclusion : To overcome the controversies and limitations of past explanatory acupuncture trials, more individualized and tailored acupuncture trials with the theoretical basis of oriental medical diagnosis is highly recommended. Also clear definition and categorization of pattern identification should be established for further active clinical researches and applications of acupuncture.

• 보건행정학회지
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• 제31권1호
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• pp.35-45
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• 2021

Background: As a descriptive study targeting 2,068 cancer patients as men of national merit in 2013, this study aims to provide the basic data for systematizing the early diagnosis and treatment of cancer by comparatively analyzing the 5-year survival rate. Methods: This study researched the survival of cancer patients through Electronic Medical Record and Patriots-Veterans Qualification Program, targeting 2,068 newly-diagnosed cancer patients verified in five veterans hospitals and consigned management system. This study verified differences between general characteristics of cancer patients as men of national merit and analyzed their survival rate. Results: The cancer patients as men of national merit were super-aged as their average age was 72.5. In the analysis of general characteristics of five major prevalent cancers, there were statistically significant differences according to age, region, cancer diagnostic path, differentiation, diagnostic method, treatment method, SEER stage, and survival period, except for the types of the man of national merit (p<0.001). The whole survival rate of cancer patients as men of national merit was 50%. The 5-year survival rates of predisposing cancers were shown as prostate cancer (79%), colorectal cancer (64%), gastric cancer (57%), liver cancer (32%), and lung cancer (12%). In the cancer diagnostic path, all the predisposing cancers showed the highest survival rate in medical examination. In the treatment method, the surgery showed the highest survival rate. The cancer patients as men of national merit showed a lower survival rate than the general cancer patients of Korea. Conclusion: It would be needed to guarantee the honorable and happy life through health recovery as special treatment of contribution and sacrifice of super-aged men of national merit by increasing the cancer survival rates through regular checkup, early diagnosis, and high-quality treatment system that could have important effects on the survival rate according to the occurrence of cancers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2131-2153
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• 2022

To achieve accurate detection of tuberculosis (TB) areas in chest radiographs, we design a chest X-ray TB area detection algorithm. The algorithm consists of two stages: the chest X-ray TB classification network (CXTCNet) and the chest X-ray TB area detection network (CXTDNet). CXTCNet is used to judge the presence or absence of TB areas in chest X-ray images, thereby excluding the influence of other lung diseases on the detection of TB areas. It can reduce false positives in the detection network and improve the accuracy of detection results. In CXTCNet, we propose a channel attention mechanism (CAM) module and combine it with DenseNet. This module enables the network to learn more spatial and channel features information about chest X-ray images, thereby improving network performance. CXTDNet is a design based on a sparse object detection algorithm (Sparse R-CNN). A group of fixed learnable proposal boxes and learnable proposal features are using for classification and location. The predictions of the algorithm are output directly without non-maximal suppression post-processing. Furthermore, we use CLAHE to reduce image noise and improve image quality for data preprocessing. Experiments on dataset TBX11K show that the accuracy of the proposed CXTCNet is up to 99.10%, which is better than most current TB classification algorithms. Finally, our proposed chest X-ray TB detection algorithm could achieve AP of 45.35% and AP50 of 74.20%. We also establish a chest X-ray TB dataset with 304 sheets. And experiments on this dataset showed that the accuracy of the diagnosis was comparable to that of radiologists. We hope that our proposed algorithm and established dataset will advance the field of TB detection.

• 대한치과교정학회지
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• 제52권2호
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• 대한한방내과학회지
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• 제45권1호
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• pp.1-10
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• 2024

Objectives: This study investigated the pattern identification (PI) and clinical index of Parkinson's disease (PD) for personalized diagnosis and treatment. Methods: This prospective observational multi-center study recruited 100 patients diagnosed with PD from two Korean medicine hospitals. To cluster new subtypes of PD, items on a PI questionnaire (heat and cold, deficiency and excess, visceral PI) were evaluated along with pulse and tongue analysis. Gait analysis was performed and blood and feces molecular signature changes were assessed to explore biomarkers for new subtypes. In addition, unified PD rating scale II and III scores and the European quality of life 5-dimension questionnaire were assessed. Results: The clinical index obtained in this study analyzed the frequency statistics and hierarchical clustering analysis to classify new subtypes based on PI. Moreover, the biomarkers and current status of herbal medicine treatment were analyzed using the new subtypes. The results provide comprehensive data to investigate new subtypes and subtype-based biomarkers for the personalized diagnosis and treatment of PD patients. Ethical approval was obtained from the medical ethics committees of the two Korean medicine hospitals. All amendments to the research protocol were submitted and approved. Conclusions: An objective and standardized diagnostic tool is needed for the personalized treatment of PD by traditional Korean medicine. Therefore, we developed a clinical index as the basis for the PI clinical evaluation of PD. Trial Registration: This trial is registered with the Clinical Research Information Service (CRIS) (KCT0008677)

• 지능정보연구
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• 제23권1호
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• pp.47-67
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• 2017

강판 표면 결함은 강판의 품질과 가격을 결정하는 중요한 요인 중 하나로, 많은 철강 업체는 그동안 검사자의 육안으로 강판 표면 결함을 확인해왔다. 그러나 시각에 의존한 검사는 통상 30% 이상의 판단 오류가 발생함에 따라 검사 신뢰도가 낮은 문제점을 갖고 있다. 따라서 본 연구는 Simultaneous MTS (S-MTS) 알고리즘을 적용하여 보다 지능적이고 높은 정확도를 갖는 새로운 강판 표면 결함 진단 시스템을 제안하였다. S-MTS 알고리즘은 단일 클래스 분류에는 효과적이지만 다중 클래스 분류에서 정확도가 떨어지는 기존 마할라노비스 다구찌시스템 알고리즘(Mahalanobis Taguchi System; MTS)의 문제점을 해결한 새로운 알고리즘이다. 강판 표면 결함 진단은 대표적인 다중 클래스 분류 문제에 해당하므로, 강판 표면 결함 진단 시스템 구축을 위해 본 연구에서는 S-MTS 알고리즘을 채택하였다. 강판 표면 결함 진단 시스템 개발은 S-MTS 알고리즘에 따라 다음과 같이 진행하였다. 첫째, 각 강판 표면 결함 별로 개별적인 참조 그룹 마할라노비스 공간(Mahalanobis Space; MS)을 구축하였다. 둘째, 구축된 참조 그룹 MS를 기반으로 비교 그룹 마할라노비스 거리(Mahalanobis Distance; MD)를 계산한 후 최소 MD를 갖는 강판 표면 결함을 비교 그룹의 강판 표면 결함으로 판단하였다. 셋째, 강판 표면 결함을 분류하는 데 있어 결함 간의 차이점을 명확하게 해주는 예측 능력이 높은 변수를 파악하였다. 넷째, 예측 능력이 높은 변수만을 이용해 강판 표면 결함 분류를 재수행함으로써 최종적인 강판 표면 결함 진단 시스템을 구축한다. 이와 같은 과정을 통해 구축한 S-MTS 기반 강판 표면 결함 진단 시스템의 정확도는 90.79%로, 이는 기존 검사 방법에 비해 매우 높은 정확도를 갖는 유용한 방법임을 보여준다. 추후 연구에서는 본 연구를 통해 개발된 시스템을 현장 적용하여, 실제 효과성을 검증할 필요가 있다.

• Imaging Science in Dentistry
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• 제50권3호
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• pp.227-236
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• 2020

Purpose: Image artifacts caused by patient motion cause problems in cone-beam computed tomography (CBCT) because they lead to distortion of the 3-dimensional reconstruction. This prospective study was performed to quantify patient movement during CBCT acquisition and its influence on image quality. Materials and Methods: In total, 412 patients receiving CBCT imaging were equipped with a wireless head sensor system that detected inertial, gyroscopic, and magnetometric movements with 6 dimensions of freedom. The type and amplitude of movements during CBCT acquisition were evaluated and image quality was rated in 7 different anatomical regions of interest. For continuous variables, significance was calculated using the Student t-test. A linear regression model was applied to identify associations of the type and extent of motion with image quality scores. Kappa statistics were used to assess intra- and inter-rater agreement. Chi-square testing was used to analyze the impact of age and sex on head movement. Results: All CBCT images were acquired in a 10-month period. In 24% of the investigations, movement was recorded (acceleration: >0.10 [m/s²]; angular velocity: >0.018 [°/s]). In all examined regions of interest, head motion during CBCT acquisition resulted in significant impairment of image quality (P<0.001). Movement in the horizontal and vertical axes was most relevant for image quality (R²>0.7). Conclusion: Relevant head motions during CBCT imaging were frequently detected, leading to image quality loss and potentially impairing diagnosis and therapy planning. The presented data illustrate the need for digital correction algorithms and hardware to minimize motion artefacts in CBCT imaging.