• Radiation Oncology Journal
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• 제32권3호
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• pp.116-124
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• 2014

Purpose: To investigate the frequency and clinical significance of detected incidental lung nodules found on computed tomography (CT) simulation images for hepatocellular carcinoma (HCC) using computer-aided diagnosis (CAD) and a physician review. Materials and Methods: Sixty-seven treatment-$na{\ddot{i}}ve$ HCC patients treated with transcatheter arterial chemoembolization and radiotherapy (RT) were included for the study. Portal phase of simulation CT images was used for CAD analysis and a physician review for lung nodule detection. For automated nodule detection, a commercially available CAD system was used. To assess the performance of lung nodule detection for lung metastasis, the sensitivity, negative predictive value (NPV), and positive predictive value (PPV) were calculated. Results: Forty-six patients had incidental nodules detected by CAD with a total of 109 nodules. Only 20 (18.3%) nodules were considered to be significant nodules by a physician review. The number of significant nodules detected by both of CAD or a physician review was 24 in 9 patients. Lung metastases developed in 11 of 46 patients who had any type of nodule. The sensitivities were 58.3% and 100% based on patient number and on the number of nodules, respectively. The NPVs were 91.4% and 100%, respectively. And the PPVs were 77.8% and 91.7%, respectively. Conclusion: Incidental detection of metastatic nodules was not an uncommon event. From our study, CAD could be applied to CT simulation images allowing for an increase in detection of metastatic nodules.

• 대한임상검사과학회지
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• 제52권4호
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• pp.310-316
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• 2020

마이크로어레이 진단 기법의 발달은 세포유전학적 관점에서, 다양한 종류의 유전학적 질병과 관련하여 새로운 정보를 제공하고, 질병에 대한 기본적인 통찰력을 제공하는데 매우 중요한 역할을 제공하고 있다. 그동안 많은 연구들에서, 마이크로어레이 기술을 활용한 인간 게놈의 유동성과 다양성을 입증해 주었으며, 게놈의 취약성을 식별하기 위한 보다 정확한 진단기법과 적절한 임상 관리 방법을 효율적으로 제공해 왔다. 앞으로 다양한 유전과 관련된 질병에 기존 세포유전학적 방법을 자동화된 마이크로어레이 방법으로 전환한다면, 보다 효율적인 방법으로 질병을 진단하고, 정확성을 향상시키며, 유전자 배열의 암호화 및 복잡한 특성을 밝히는데 매우 중요한 역할을 할 것으로 생각된다. 또한 이 분석 기법을 활용하여 게놈과 인간의 건강, 질병과의 관계를 분석하여 다양한 정보를 미리 제공하여 질병을 예방하고, 질병의 진단 및 치료에도 도움이 될 수 있는 새로운 혁명을 일으킬 수 있을 것으로 기대된다.

• 대한한의학회지
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• 제42권4호
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• pp.102-119
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• 2021

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, using a fully automated facial shape analysis system, we show that facial morphological features are associated with cold pattern. Methods: The facial morphological features calculated from 68 facial landmarks included the angles, areas, and distances between the landmark points of each part of the face. Cold pattern severity was determined using a questionnaire and the cold pattern scores (CPS) were used for analysis. The association between facial features and CPS was calculated using Pearson's correlation coefficient and partial correlation coefficients. Results: The upper chin width and the lower chin width were negatively associated with CPS. The distance from the center point to the middle jaw and the distance from the center point to the lower jaw were negatively associated with CPS. The angle of the face outline near the ear and the angle of the chin line were positively associated with CPS. The area of the upper part of the face and the area of the face except the sensory organs were negatively associated with CPS. The number of facial morphological features that exhibited a statistically significant correlation with CPS was 37 (unadjusted). Conclusions: In this study of a Korean population, subjects with a high CPS had a more pointed chin, longer face, more angular jaw, higher eyes, and more upward corners of the mouth, and their facial sensory organs were relatively widespread.

• 대한한의학회지
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• 제44권4호
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• pp.136-149
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• 2023

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, we proposed a model to quantitatively classify cold sensitivity using a fully automated facial image analysis system. Methods: We investigated cold sensitivity in 452 subjects. Cold sensitivity was determined using a questionnaire and the Cold Pattern Score (CPS) was used for analysis. Subjects with a CPS score below the first quartile (low CPS group) belonged to the cold non-sensitivity group, and subjects with a CPS score above the third quartile (high CPS group) belonged to the cold sensitivity group. After splitting the facial images into train/validation/test sets, the train and validation set were input into a convolutional neural network to learn the model, and then the classification accuracy was calculated for the test set. Results: The classification accuracy of the low CPS group and high CPS group using facial images in all subjects was 76.17%. The classification accuracy by sex was 69.91% for female and 62.86% for male. It is presumed that the deep learning model used facial color or facial shape to classify the low CPS group and the high CPS group, but it is difficult to specifically determine which feature was more important. Conclusions: The experimental results of this study showed that the low CPS group and the high CPS group can be classified with a modest level of accuracy using only facial images. There was a need to develop more advanced models to increase classification accuracy.

• Korean Journal of Radiology
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• 제22권4호
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• pp.612-623
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• 2021

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988-0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618-0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion: The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.

• Tuberculosis and Respiratory Diseases
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• 제74권6호
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• pp.251-255
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• 2013

Tuberculosis (TB) is one of the largest health problems in the world today. And the incidence of nontuberculous mycobacteria (NTM) lung disease appears to be increasing worldwide. Recently, an automated, nucleic acid amplification assay for the rapid detection of both Mycobacterium tuberculosis and rifampin resistance was developed (Xpert MTB/RIF). And fixed-dose combinations of anti-TB drugs and linezolid have been introduced in the treatment of TB. And new NTM species, named Mycobacterium massiliense, which is very closely related to Mycobacterium abscessus was reported. In this review, these recent advances in the diagnosis and treatment of TB and clinical characteristics of M. massiliense lung disease are discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제20권3호
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• pp.175-202
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• 2016

Ultrasound imaging is a widely used tool for visualizing human body's internal organs and quantifying clinical parameters. Due to its advantages such as safety, non-invasiveness, portability, low cost and real-time 2D/3D imaging, diagnostic ultrasound industry has steadily grown. Since the technology advancements such as digital beam-forming, Doppler ultrasound, real-time 3D imaging and automated diagnosis techniques, there are still a lot of demands for image quality improvement, faster and accurate imaging, 3D color Doppler imaging and advanced functional imaging modes. In order to satisfy those demands, mathematics should be used properly and effectively in ultrasound imaging. Mathematics has been used commonly as mathematical modelling, numerical solutions and visualization, combined with science and engineering. In this article, we describe a brief history of ultrasound imaging, its basic principle, its applications in obstetrics/gynecology, cardiology and radiology, domestic-industrial products, contributions of mathematics and challenging issues in ultrasound imaging.

• 대한의용생체공학회:의공학회지
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• 제16권2호
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• pp.121-128
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• 1995

Information about retinal blood vessels can be used in grading disease severity or as part of the process of automated diagnosis of diseases with ocular menifestations. In this paper, we address the problem of detecting retinal blood vessels and optic disk (papilla) in eye-fundus images. We introduce an algorithm for feature extraction based on Fuzzy Clustering algorithm (fuzzy c-means). A method of finding the optic disk (papilla) is proposed in the eye-fundus images. Additionally, the inrormations such as position and area of the optic disk are extracted. The results are compared to those obtained from other methods. The automatic detection of retinal blood vessels and optic disk in the eye-rundus images could help physicians in diagnosing ocular diseases.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2000년도 추계종합학술대회
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• pp.642-646
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• 2000

The use of neural-fuzzy system to model mesh seam welding is described in this paper. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current torch travel speed and the pressure and so on. The relationship between the welding parameters and weld quality is not a direct one, md' in addition, the effect of the weld parameter variables are not independent of the each other. The effectiveness of the proposed neuro-fuzzy algorithms is demonstrated by computer simulations.

• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.351-360
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• 1989

This paper describes the design of portable arrhythmia monitor and associated algorithm for automated diagnosis based-on microcomputer in the ambulatory ECG recording, analysis, and transmitting to a hospital host computer immediately through the telephone system. The device differs from Molter recorder in that it does not store normal ECG signals but captures and alarms the ECG during suspected abnormal periods and selected temporal epochs to a central hospital site. This porta file arrhythmia monitor makes use of a general purpose computer and software will be changed to meet the custom requirements of individual physicians and patients. At present it is very obvious that each cardiologist has his own method of analyzing ECG recordings and utilizes past experience more than the firm quantitative analysis of data.