• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.45 no.6
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• pp.302-308
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• 2019

Fractures of the styloid process of the temporal bone may occur with or without an obvious relation to trauma. The incidence of either isolated styloid process fracture or in combination with mandibular fractures is rare, and such occurrences are often misdiagnosed or neglected. A fractured styloid when displaced may impinge on adjacent vital structures, leading to neurological or vascular symptoms that vary according to the anatomical structure compressed. Styloid process fractures associated with atlas/C1 fractures have also been rarely reported in the literature. In this review of literature, the majority of patients was treated conservatively, as few demonstrated the necessity of surgical intervention. There is a definitive need for a protocol to recognize and classify styloid fractures to plan for further treatment. The aim of this review was to achieve a comprehensive understanding of all types of styloid fractures, determine the clinical severity of symptoms, and to consider management and prognosis. In addition, a new classification of cervico-stylo-mandibular fractures is proposed based on important evidence in the literature regarding clinical and radiographic factors that might influence the treatment and prognosis of such fractures.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.21-32
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• 2022

Early-stage diagnosis of Alzheimer's Disease (AD) from Cognitively Normal (CN) patients is crucial because treatment at an early stage of AD can prevent further progress in the AD's severity in the future. Recently, computer-aided diagnosis using magnetic resonance image (MRI) has shown better performance in the classification of AD. However, these methods use a traditional machine learning algorithm that requires supervision and uses a combination of many complicated processes. In recent research, the performance of deep neural networks has outperformed the traditional machine learning algorithms. The ability to learn from the data and extract features on its own makes the neural networks less prone to errors. In this paper, a dense neural network is designed for binary classification of Alzheimer's disease. To create a classifier with better results, we studied result of different activation functions in the prediction. We obtained results from 5-folds validations with combinations of different activation functions and compared with each other, and the one with the best validation score is used to classify the test data. In this experiment, features used to train the model are obtained from the ADNI database after processing them using FreeSurfer software. For 5-folds validation, two groups: AD and CN are classified. The proposed DNN obtained better accuracy than the traditional machine learning algorithms and the compared previous studies for AD vs. CN, AD vs. Mild Cognitive Impairment (MCI), and MCI vs. CN classifications, respectively. This neural network is robust and better.

• Journal of the Korean Society of Physical Medicine
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• v.14 no.4
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• pp.45-53
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• 2019

PURPOSE: This study examined the differences in the trunk impairment scores according to the levels of the gross motor classification system by evaluating trunk control in children with spastic cerebral palsy using the index of trunk impairment. In addition, the characteristics of trunk control disabilities were investigated according to the cerebral palsy type. METHODS: The subjects were 49 children (mean age 8.57±1.83 years, 11 with hemiplegia, 26 with diplegia, and 12 with quadriplegia) with spastic cerebral palsy levels I to IV under the gross motor function classification system (GMFCS). The coordination and balance of the children with cerebral palsy were evaluated using the index for trunk impairment. Statistical analyses were performed using a Kruskal-Wallis test, and Bonferroni analyses were used as a post-hoc comparison for any significant results. RESULTS: The median of the total scores of trunk impairment was 13 (range, 9-17), which was 56% of the maximum score. The total score of trunk impairment and subscales differed significantly according to the disease severity and type of motor disability. The scores for children with quadriplegia were the lowest compared to children with hemiplegia and diplegia. CONCLUSION: Trunk control function in children with spastic cerebral palsy was reduced, and varied according to the disease severity and types of motor disabilities. The degree of trunk impairment differed from the trunk control ability according to the degree of motor disability of children with cerebral palsy.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.2
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• pp.99-111
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• 2021

Objectives: It is unclear whether the extent of intraoral mucosa defects in patients with medication-related osteonecrosis of the jaw indicates disease severity. Therefore, this study investigated whether mucosal lesions correlate with the true extent of osseous defects in stage I patients. Materials and Methods: Retrospectively, all patients with stage I medication-related osteonecrosis of the jaw who underwent surgical treatment between April 2018 and April 2019 were enrolled. Preoperatively, the extent of their mucosal lesions was measured in clinical evaluations, and patients were assigned to either the visible or the probeable bone group. Intraoperatively, the extent of necrosis was measured manually and with fluorescence. Results: Fifty-five patients (36 female, 19 male) with 86 lesions (46 visible bone, 40 probeable bone) were enrolled. Intraoperatively, the necrotic lesions were significantly larger (P<0.001) than the preoperative mucosal lesions in both groups. A significant (P<0.05) but very weak (R2<0.2) relationship was noted between the extent of the mucosal lesions and the necrotic bone area. Conclusion: Preoperative mucosal defects (visible or probeable) in patients with medication-related osteonecrosis of the jaw do not indicate the extent of bone necrosis or disease severity.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.2
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• pp.251-258
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• 2019

Objective: Chronic obstructive pulmonary disease(COPD) is characterized by persistent airflow limitations associated with chronic inflammatory response due to noxious particles or gases in the lung. Inflammation and oxidative stress are associated with COPD. The aim of this study was to evaluate the relationship among inflammation, oxidative stress, and airflow limitation severity in retired miners with COPD. Methods: The levels of serum high-sensitivity C-reactive protein(hsCRP) as a biomarker for inflammation, degree of reactive oxygen metabolites(dROMs) and biological antioxidants potential(BAP) in plasma as biomarkers for oxidative stress were measured in 211 male subjects with COPD. Degree of airflow limitation severity as determined by spirometry was divided into three grades grouped according to the classification of the Global Initiatives for Obstructive Lung Disease(GOLD)(1, mild; 2, moderate; $3{\leq}$, severe or more) using a fixed ratio, post- bronchodilator $FEV_1/FVC$ < 0.7. Results: Mean levels of dROMs significantly increased in relation to airflow limitation severity(GOLD 1, 317.8 U.CARR vs. GOLD 2, 320.3 U.CARR vs. GOLD $3{\leq}$, 350.9 U.CARR, p=0.047) and dROMs levels were correlated with serum hsCRP levels(r=0.514, p<0.001). Mean levels of hsCRP were higher in current smokers(non-smoker, 1.47 mg/L vs. smoker, 2.34 mg/L, p=0.006), and tended to increase with degree of airflow limitation severity(p=0.071). Mean levels of BAP were lower in current smokers(non-smoker, $1873{\mu}mol/L$ vs. smoker, $1754{\mu}mol/L$, p=0.006). Conclusions: These results suggest that inflammation and oxidative stress are related to airflow limitation severity in retired miners with COPD, and there was a correlation between inflammation and oxidative stress.

• Tuberculosis and Respiratory Diseases
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• v.44 no.3
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• pp.639-648
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• 1997

Background : Arterial hypoxemia has been noted in patients with liver cirrhosis because of bronchial vessel dilatation. Cabenes et al. reported that bronchial hyperresponsiveness to the metacholine inhalation was observed in patients of left side heart failure, he suggested that one of the mechanism was bronchial vessel dilatation. We hypothesized that patients of liver cirrhosis might have bronchial hyperresponsiveness to metacholine inhalation due to portal hypertension. We evaluate the relationship between bronchial responsiveness and severity of liver cirrhosis, severity of portal hypertension. Methods : In the 22 patients of the liver cirrhosis with clinical portal hypertension, metacholine provocation test was done and determined $PC_{20}FEV1$. We classified liver cirrhosis according to Pugh-Child classification. Esophagogastroscopies were performed for the evaluation of the relationship between bronchial hyperresponsiveness and severity of esophageal varix. Results : In the 22 cases of the liver cirrhosis with clinical portal hypertension. The causes of liver cirrhosis, alcoholic hepatitis was 9 cases, hepatitis B virus was 12 cases, hepatitis C virus was 1 case, and 151 cases (68.18%) of total 22 cases were positive in metacholine provocation test. In positive cases. There was no significant relationship between $PC_{20}FEV1$ and severity of liver cirrhosis which were classified by Pugh-Child classification or severity of esophageal varix(p<0.05). Conclusion : we observed that bronchial responsiveness to metacholine increased in the patients of liver cirrhosis and there was no significant relationship between the severity of liver cirrhosis and the severity of esophageal varix.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1015-1026
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• 2019

Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.

• Asian Oncology Nursing
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• v.5 no.1
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• pp.3-10
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• 2005

Back ground: Nurses now occupy one third of all hospital human resources. Therefore, efficient management of nursing manpower is getting more important. While it is very clear that nursing workload requirement analysis and patient severity classification should be done first for the efficient allocation of nursing workforce, these processes have been conducted manually with ad hoc rule. Purposes: This study was tried to make a predict model for patient classification according to nursing need. We tried to find the easier and faster method to classify nursing patients that can help efficient management of nursing manpower. Methods: The nursing patient classifications data of the hospitalized cancer patients in one of the biggest cancer center in Korea during 2003.1.1-2003.12.31 were assessed by trained nurses. This study developed a prediction model and analyzing nursing needs by data mining techniques. Patients were classified by three different data mining techniques, (Logistic regression, Decision tree and Neural network) and the results were assessed. Results: The data set was created using 165,073 records of 2,228 patients classification database. Main explaining variables were as follows in 3 different data mining techniques. 1) Logistic regression : age, month and section. 2) Decision tree : section, month, age and tumor. 3) Neural network : section, diagnosis, age, sex, metastasis, hospital days and month. Among these three techniques, neural network showed the best prediction power in ROC curve verification. As the result of the patient classification prediction model developed by neural network based on nurse needs, the prediction accuracy was 84.06%. Conclusion: The patient classification prediction model was developed and tested in this study using real patients data. The result can be employed for more accurate calculation of required nursing staff and effective use of labor force.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.15 no.4
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• pp.485-494
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• 2008

Purpose: In this study, relationships between symptom experience and quality of life in a cross-sectional sample of patients with Atrial Fibrillation (AF) were investigated. Methods: This descriptive study involved a convenience sample of AF patients from S university hospital, C city. One hundred and two AF patients completed psychometric validated measures of AF related symptoms and quality of life. Descriptive statistics and Pearson correlation coefficients with SPSS WIN 14.0 were used for data analysis. Results: Of 16 atrial arrhythmia-related symptoms, the patients reported 'tiredness' as the most frequent and 'shortness of breath' as the most severe. The level of overall quality of life for patients with AF was 53.92. There were significant differences in symptom frequency according to religion, New York Heart Association (NYHA) classification and left ventricular ejection fraction ; symptom severity according to monthly income and stroke ; quality of life according to age, job, alcohol intake, NYHA class and stroke. Quality of life for these patients was positively correlated with symptom frequency and symptom severity. Conclusions: This study demonstrated that patients with more frequent and severe symptoms perceive poorer quality of life than patients with less frequent and less severe symptoms. Symptom experience should be assessed early to improve quality of life for patients.

• Journal of Veterinary Clinics
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• v.34 no.5
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• pp.313-317
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• 2017

Symmetric dimethylarginine (SDMA) is a new renal biomarker for kidney function. It is almost exclusively eliminated by renal filtration. The purpose of this retrospective study was to evaluate the changes in serum ceatinine (CREA), blood urea nitrogen (BUN) and SDMA concentrations in dogs with chronic mitral valve insufficiency (CMVI), according to the severity of CMVI. The evaluation of the severity of CMVI was performed according to the American College of Veterinary Internal Medicine (ACVIM) classification of heart failure. The dogs were classified into two groups: group 1 (ACVIM B; n = 11) and group 2 (ACVIM C; n = 15). In dogs with advanced CMVI, the serum SDMA concentrations were significantly increased above the normal reference range and were independent of body weight (BW), systolic blood pressure (SBP), or sex. No dog in either group had higher serum CREA concentrations than the upper limit. The serum SDMA concentration may be a better renal marker than serum CREA concentrations for the early diagnoses of renal dysfunction in dogs with CMVI.