• Journal of Sasang Constitutional Medicine
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• v.23 no.4
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• pp.458-470
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• 2011

1. Objectives Vocal characteristics are commonly considered as an important factor in determining the Sasang constitution and the health condition. We have tried to find out the classification procedure to distinguish the constitution objectively and quantitatively by analyzing the characteristics of subject's voice without noise and error. 2. Methods In this study, we extract the vocal features from voice selected with prior information, remove outliers, minimize the correlated features, correct the features with normalization according to gender and age, and make the discriminant functions that are adaptive to gender and age from the features for improving diagnostic accuracy. 3. Results and Conclusions Finally, the discriminant functions produced about 45% accuracy to classify the constitution for every age interval and every gender, and the diagnostic accuracy was meaningful as the result from only the voice.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2859-2870
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• 2022

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution. We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.665-682
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• 2005

The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.5
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• pp.553-560
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• 2003

On-site diagnosis of chiller performance is an essential step fur energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for this purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.374-381
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• 1991

As a diagnostic image of hospitl, the utilization of digital image is steadily increasing. Image coding is indispensable for storing and compressing an enormous amount of diagnostic images economically and effectively. In this paper adaptive two stage vector quantization based on Kohonen's neural network for the compression of cardioangiography among typical angiography of radiographic image sequences is presented and the performance of the coding scheme is compare and gone over. In an attempt to exploit the known characteristics of changes in cardioangiography, relatively large blocks of image are quantized in the first stage and in the next stage the bloks subdivided by the threshold of quantization error are vector quantized employing the neural network of frequency sensitive competitive learning. The scheme is employed because the change produced in cardioangiography is due to such two types of motion as a heart itself and body motion, and a contrast dye material injected. Computer simulation shows that the good reproduction of images can be obtained at a bit rate of 0.78 bits/pixel.

• Journal of Preventive Medicine and Public Health
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• v.31 no.3 s.62
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• pp.471-480
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• 1998

This study was undertaken in order to estimate the accuracy of disease code of the Korean National Medical Insurance Data and disease the characteristics related to the accuracy. To accomplish these objectives, 2,431 cases coded as notifiable acute communicable diseases (NACD) were randomly selected from 1994 National Medical Insurance data file and family medicine specialists reviewed the medical records to confirm the diagnostic accuracy and investigate the related factors. Major findings obtained from this study are as follows : 1. The accuracy rate of disease code of NACD in National Medical Insurance data was very low, 10.1% (95% C.I. : 8.8-11.4). 2. The reasons of inaccuracy in disease code were 1) claiming process related administrative error by physician and non-physician personnel in medical institutions (41.0%), 2) input error of claims data by key punchers of National Medical Insurer (31.3%) and 3) diagnostic error by physicians (21.7%). 3. Characteristics significantly related with lowering the accuracy of disease code were location and level of the medical institutions in multiple logistic regression analysis. Medical institutions in Seoul showed lower accuracy than those in Kyonngi, and so did general hospitals, hospitals and clinics than tertiary hospitals. Physician related characteristics significantly lowering disease code accuracy of insurance data were sex, age group and specialty. Male physicians showed significantly lower accuracy than female physicians; thirties and fortieg age group also showed significantly lower accuracy than twenties, and so did general physicians and other specialists than internal medicine/pediatric specialists. This study strongly suggests that a series of policies like 1) establishment of peer review organization of National Medical Insurance data, 2) prompt nation-wide expansion of computerized claiming network of National Medical Insurance and 3) establishment and distribution of objective diagnostic criteria to physicians are necessary to set up a national disease surveillance system utilizing National Medical Insurance claims data.

• Progress in Medical Physics
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• v.7 no.1
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• pp.3-7
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• 1996

The accuracy in target localization of CT, MR, and digital angiography were investigated for stereotactic radiosurgery. The images using CT and MR were obtained out of geometrical phantom which was designed to produce exact coordinates of several points within a 0.lmm error range. The slice interval was 3mm and FOV was 35cm for CT and 28cm for MR. These images were transferred to treatment planning computer using TCP/IP in forms of GE format. Measured 3-D coordinates of these images from planning computer were compared to known values by geometrical phantom. Anterior-posterior and lateral films were taken by digital angiography for measurement of spatial accuracy. Target localization errors were 1.2${\pm}$0.5mm with CT images, 1.7${\pm}$0.4mm with MR-coronal images, and 2.1${\pm}$0.7mm with MR-sagittal images. But, in case of MR-axial images, the target localization error was 4.7${\pm}$0.9mm. Finally, the target localization error of digital angiography was 0.9${\pm}$0.4mm. The accuracy of diagnostic machines such as CT, MR, and angiography depended on their resolutions and distortions. The target localization error mainly depended on the resolution due to slice interval with CT and the image distortion as well as the resolution with MR However, in case of digital angiography, the target localization error was closely related to the distortion of fiducial markers. The results of our study should be considered when PTV (Planning Target Volume) was determined.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.13 no.1
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• pp.93-103
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• 2002

The aim of this study is to examine the diagnostic profiles and related clinical variables of children with attention and hyperactivity in psychiatric outpatient clinic. Seventy one children with age range of 5 to 14 were diagnosed by DSM-IV, and assessment battery including KEDI-WISC, KPI-C, ADS(ADHD Diagnostic System) were completed. The subjects were divided into 3 diagnostic groups：ADHD only(n=17), ADHD comorbid(n=27), Other diagnosis(n=27). The results were as follows：In ADHD comorbid group, tic disorder, developmental language disorder, borderline intellectual function, oppositional defiant/conduct disorder, and learning disorder were combined in descending order. Other diagnosis group consisted of tic disorder, borderline intellectual function, depression/anxiety, oppositional defiant/conduct disorder, and others. There were significant differences in IQ, PIQ, and VIQ among the three groups, and ADHD only group showed higher scores of IQ and VIQ than ADHD comorbid group. On the KPI-C, there were no significant differences in all subscales among the three groups. On the visual ADS, omission error and sensitivity showed significant differences among the three groups, and ADHD comorbid group represented higher omission error and lower sensitivity than other diagnostic group. The findings indicated that the inattention and hyperactivity symptoms could be diagnosed into diverse psychiatric disorders in child psychiatry, and ADHD children with comorbidity will show more problems in academic performance and school adjustment.

• Journal of Korean Medical classics
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• v.26 no.4
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• pp.385-396
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• 2013

Zhang Yuan-Su(張元素) was a doctor of the Jin(金) period, who was followed by Li Dong-Yuan(李東垣) and Wang Hao-Gu(王好古), creating the Yishui School(易水學派). The most notable aspect of his theory is the internal organs(臟腑)-based diagnostic system. He organized previous methods based on the internal organs and applied the same methodology in treatment as well. The Zangfu-biaoben-xushi-hanre-yongyaoshi(臟腑標本虛實寒熱用藥式) is one of his major publications in which diagnostic and treatment methods are organized in a simple manner. In this book, the diseases of the organs are divided into the tip and root(標本). This paper investigates the standards of categorizing tip and root diseases through analysis of all symptoms of both tip and root diseases of the five internal organs. Then the results of the analysis were used in grasping the similarities and tendencies of the root disease and tip disease. Conclusively, root diseases indicate disorder in the internal organs themselves. Tip diseases indicate disorder in the channels and collaterals, diseases caused by exterior pathogens or symptoms that manifest in the exteriors of the body. Such categorization is thought to have been established to eliminate diagnostic error that could occur from using the same expressive means in describing symptoms with different causes, in the process of forming an uncomplicated diagnostic system.

• Annals of Clinical Neurophysiology
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• v.24 no.1
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• pp.7-16
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• 2022

Background: There is inadequate information on the validation of diabetic microvascular complications in the Korean National Health Insurance Service data set. We aimed to validate the diagnostic algorithms regarding the nephropathy, neuropathy, and retinopathy of diabetes. Methods: From various secondary and tertiary medical centers, we selected 6,493 patients aged ≥ 40 years who were diagnosed with diabetic microvascular complications more than once based on codes in the 10th version of the International Classification of Diseases (ICD-10). During 2019 and 2020, we randomly selected the diagnoses of 200 patients, 100 from each of two hospitals. The positive predictive value (PPV), negative predictive value, error rate, sensitivity, and specificity were determined for each diabetic microvascular complication according to the ICD-10 codes, laboratory findings, diagnostic studies, and treatment procedure codes. Results: Among the 200 patients who visited the hospital more than once and had the diagnostic codes of diabetic microvascular complications, 142, 110, and 154 patients were confirmed to have the gold standard of diabetic nephropathy (PPV, 71.0%), diabetic neuropathy (PPV, 55.0%), and diabetic retinopathy (PPV, 77.0%), respectively. The PPV and specificity of diabetic nephropathy (PPV, 71.0-81.4%; specificity, 10.3-53.4%), diabetic neuropathy (PPV, 55.0-81.3%; specificity, 66.7-76.7%) and diabetic retinopathy (PPV, 77.0-96.6%; specificity, 2.2-89.1%) increased after combining them with the laboratory findings, diagnostic studies, and treatment procedures codes. These change trends were observed similarly for both hospitals. Conclusions: Defining diabetic microvascular complications using ICD-10 codes and their related examination codes may be a feasible method for studying diabetic complications.