• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Archives of Plastic Surgery
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• v.49 no.3
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• pp.360-364
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• 2022

Although capsular contracture represents one of the most important complications after breast augmentation, local inflammation and fibrosis can lead, to capsular calcification, an often-forgotten radiological sign of capsular contracture. In this article, the authors present a clinical case of breast implant calcification in an 81-year-old patient. Although this complication has been rarely described, the literature was reviewed to clarify the role of the local microenvironment in capsular contracture and calcification. At present, capsular contracture patients are classified using the conventional Baker score and the histological Wilflingseder classification. As it was not possible to consider capsular calcification when classifying our patient using the traditional scores, the authors propose an updated version of the current scale.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.193-206
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• 2008

Medical diagnosis can be considered a classification task which classifies disease types from patient's condition data represented by a set of pre-defined attributes. This study proposes a hybrid genetic algorithm based classification method to develop classifiers for multidimensional pattern classification problems related with medical decision making. The classification problem can be solved by identifying separation boundaries which distinguish the various classes in the data pattern. The proposed method fits a finite number of regional agents to the data pattern by combining genetic algorithms and local adaptive operations. The local adaptive operations of an agent include expansion, avoidance and relocation, one of which is performed according to the agent's fitness value. The classifier system has been tested with well-known medical data sets from the UCI machine learning database, showing superior performance to other methods such as the nearest neighbor, decision tree, and neural networks.

• Perspectives in Nursing Science
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• v.6 no.1
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• pp.39-53
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• 2009

The purpose of this study is to grasp the present system of Advanced Practice Nurse(APN) and to suggest strategies for enhancing the recognition of APNs institutionally in Korea. We searched and reviewed literature and materials about the APN development process and present situation and related laws. We recognized that there were many kinds of problems in the APN system of Korea: a weak support from health care system, obscured classification of APN's services, confusion of qualifications, and lack of compensation from the national health insurance system. We should, therefore, identity the list of Korean APN's services and provide further studies about patient's outcome cared by APNs. Also, there is a need to create a demand for APNs to keep the quality of services guaranteed by APN. APN system must be established to progress forward in order to provide good benefits for the people.

• Journal of the korean academy of Pediatric Dentistry
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• v.25 no.4
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• pp.704-709
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• 1998

Amelogenesis imperfecta represents a group of hereditary conditions that manifest enamel defects without evidence of generalized or systemic disorders. These enamel disorders are apparently heterogeneous in the basic chemical structure, resulting in a diverse presentation of clinical characteristics. The reported prevalence of amelogenesis imperfecta varies from 1 in 14,000-16,000 to 1.4 in 1,000 depending on specific population studied with the autosomal dominant hypocalcification type of amelogenesis imperfecta believed to be the least prevalent. The most widely accepted current classification system for delineating the amelogenesis imperfecta types considers the mode of inheritance and clinical manifestations. Three major groups are recognized; hypoplastic, hypocalcified, and hypomaturation types. Delineating specific types of amelogenesis imperfecta can be confusing due to the phenotypical similarity of many forms and that the most recent classification lists 14 different types. A 12 year-old female patient came to our pediatric dentistry clinic complaining of the ugly shape and color of her teeth, especially the upper front area. Although the goal of the treatment was mainly focused on the improvement of patient's esthetics, longevity of the restorations was also considered in selecting the appropriate restorative system, resin jacket crown, which can satisfy the both aspects.

• Advances in pediatric surgery
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• v.12 no.2
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• pp.137-146
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• 2006

Pediatric surgery could establish a definitive position in the medical field on the basis of a stable patient population. Neonatal surgery, the core of pediatric surgery, requires highly skilled surgeons. However, recent advancement of prenatal diagnosis followed by intervention and decreased birth rate has resulted in a significant decrease in the neonatal surgical population and the number of surgical operations. The purpose of this study is to examine the outcome of neonatal surgeries and to propose a guide for the future surgeries. A total of 359 neonatal surgical patients operated upon at the Department of Surgery, Ewha Medical Center, during past 21 years were studied. The study period hasbeen divided into two time periods: from 1983 to 1993 and from 1994 to 2004. Analysis was based on the Clinical Classification System and mortality pattern, frequency of disorders, occurrence and cause of death, and other changes. Neonatal surgery was 6.4 % of all pediatric surgery during the total 21 year period, 9.9 % in the first period and 4.8 % in the second. Male to female ratio increased from 2.7:1 to 2.1:1. The overall mortality was 6.7 %, and there was significant decrease from 7.4 % in the first period to 6.0 % in the second. The clinical classification system (CCS) for death cases included class II 2, III 4, and IV 7 during the first period and class III 3, and IV 8 during the second, respectively. According to the mortality pattern by Hazebroek, there were 6 preventable death cases during the first period, and only one in the second, and 2 non-preventable death cases during the first period and 8 in second, respectively. Although the patients in the second period had more serious diseases, surgical mortality has been decreased in the second period, which may be the result of improved surgery methods for newborns and advanced patient care.

• The Journal of Korean Physical Therapy
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• v.5 no.1
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• pp.47-60
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• 1993

This study was conducted to investigate the changes diseases of physical therapy patient. Through the analysis, of total 2,902 cases in one university hospital and one general hospital in Taegu, of which 1,619 cases for 1989 and 1,283 cases for 1981. The physical records were analyzed in terms of sex, age, pattern in PT diseases, fee, and medical department of PT. The international classification of Diseases, 9th revision was used fer the study. Major results are as follows : 1. The ratio of male me female nae 1.51 to 1 in 1989, 1.53 to 1 in 1991. The proportion of the elderly over 60 was $15.6\%$ in 1989, $22.0\%$ in 1989. And the age groups of 50-59 years ranked the first an years. 2. As to the PT patients of medical department, Orthopaedics$(50.3\%)$, Neurosurgery$(28.1\%)$. Neuromedicine$(8.0\%)$. Plastic surgery$(4.4\%)$, and Dentry$(3.2\%)$ in that order in 1989. On the other hand, Orthopaedics$(51.2\%)$, Neurosurgery$(22.1\%)$, Neuromedicine$(9.6\%)$, Plastic surgery$(6.5\%)$, and Internal medicine$(6.5\%)$ in that order in 1991. 3. No significant difference was observed by season of PT patients, but winter (December, January and February) ranked the first all years. 4. No significant difference was observed changes in diseases as for the 56 international classification of diseases of PT patients, Diseases of the musculoskeletal system and connective tissue occupied the largest proportion all years. Fractures increased from $21.4\%$ in 1989, $24.5\%$ in 1991. On the other hand, Diseases of the nervous system remarkably increased from $8.9\%$ in 1989, $19.7\%$ in 1991.

• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.71-84
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• 2011

Pervasive applications such as digital memories or patient monitors collect a vast amount of data. One key challenge in these systems is how to extract interesting or unusual information. Because users cannot anticipate their future interests in the data when the data is stored, it is hard to provide appropriate indexes. As location-tracking technologies, such as global positioning system, have become ubiquitous, digital cameras or other pervasive systems record location information along with the data. In this paper, we present an automatic approach to identify unusual data using location information. Given the location information, our system identifies unusual days, that is, days with unusual mobility patterns. We evaluated our detection system using a real wireless trace, collected at wireless access points, and demonstrated its capabilities. Using our system, we were able to identify days when mobility patterns changed and differentiate days when a user followed a regular pattern from the rest. We also discovered general mobility characteristics. For example, most users had one or more repeating mobility patterns, and repeating mobility patterns did not depend on certain days of the week, except that weekends were different from weekdays.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.373-382
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• 2018

Since epileptic seizure is unpredictable and paroxysmal, an automatic system for seizure detecting could be of great significance and assistance to patients and medical staff. In this paper, a novel method is proposed for multichannel patient-specific seizure detection applying the earth mover's distance (EMD) in scalp EEG. Firstly, the wavelet decomposition is executed to the original EEGs with five scales, the scale 3, 4 and 5 are selected and transformed into histograms and afterwards the distances between histograms in pairs are computed applying the earth mover's distance as effective features. Then, the EMD features are sent to the classifier based on the Bayesian linear discriminant analysis (BLDA) for classification, and an efficient postprocessing procedure is applied to improve the detection system precision, finally. To evaluate the performance of the proposed method, the CHB-MIT scalp EEG database with 958 h EEG recordings from 23 epileptic patients is used and a relatively satisfactory detection rate is achieved with the average sensitivity of 95.65% and false detection rate of 0.68/h. The good performance of this algorithm indicates the potential application for seizure monitoring in clinical practice.