• Genomics & Informatics
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• v.15 no.4
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• pp.156-161
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• 2017

Transcriptome analysis has been widely used to make biomarker panels to diagnose cancers. In breast cancer, the age of the patient has been known to be associated with clinical features. As clinical transcriptome data have accumulated significantly, we classified all human genes based on age-specific differential expression between normal and breast cancer cells using public data. We retrieved the values for gene expression levels in breast cancer and matched normal cells from The Cancer Genome Atlas. We divided genes into two classes by paired t test without considering age in the first classification. We carried out a secondary classification of genes for each class into eight groups, based on the patterns of the p-values, which were calculated for each of the three age groups we defined. Through this two-step classification, gene expression was eventually grouped into 16 classes. We showed that this classification method could be applied to establish a more accurate prediction model to diagnose breast cancer by comparing the performance of prediction models with different combinations of genes. We expect that our scheme of classification could be used for other types of cancer data.

• Journal of Gastric Cancer
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• v.15 no.3
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• pp.183-190
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• 2015

Purpose: The Lauren classification system is a very commonly used pathological classification system of gastric adenocarcinoma. A recent study proposed that the Lauren classification should be modified to include the anatomical location of the tumor. The resulting three types were found to differ significantly in terms of genomic expression profiles. This retrospective cohort study aimed to evaluate the clinical significance of the modified Lauren classification (MLC). Materials and Methods: A total of 677 consecutive patients who underwent curative gastrectomy from January 2005 to December 2007 for histologically confirmed gastric cancer were included. The patients were divided according to the MLC into proximal non-diffuse (PND), diffuse (D), and distal non-diffuse (DND) type. The groups were compared in terms of clinical features and overall survival. Multivariate analysis served to assess the association between MLC and prognosis. Results: Of the 677 patients, 48, 358, and 271 had PND, D, and DND, respectively. Their 5-year overall survival rates were 77.1%, 77.7%, and 90.4%. Compared to D and PND, DND was associated with significantly better overall survival (both P<0.01). Multivariate analysis showed that age, differentiation, lympho-vascular invasion, T and N stage, but not MLC, were independent prognostic factors for overall survival. Multivariate analysis of early gastric cancer patients showed that MLC was an independent prognostic factor for overall survival (odds ratio, 5.946; 95% confidence intervals, 1.524~23.197; P=0.010). Conclusions: MLC is prognostic for survival in patients with gastric adenocarcinoma, in early gastric cancer. DND was associated with an improved prognosis compared to PND or D.

• Journal of Korean Biological Nursing Science
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• v.16 no.4
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• pp.342-348
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• 2014

Purpose: The purpose of this study was to examine the effects of pressure ulcer classification system education on hospital nurses' knowledge and visual discrimination ability of pressure ulcer classification system and incontinence-associated dermatitis. Methods: One group pre- and post-test was used. A convenience sample of 96 nurses participating in pressure ulcer classification system education, were enrolled in single institute. The education program was composed of a 50-minute lecture on pressure ulcer classification system and case-studies. The pressure ulcer classification system and incontinence-associated dermatitis knowledge test and visual discrimination tool, consisting of 21 photographs including clinical information were used. Paired t-test was performed using SPSS/WIN 18.0. Results: The overall mean difference of pressure ulcer classification system knowledge (t=4.67, p<.001) and visual discrimination ability (t=10.58, p<.001) were statistically and significantly increased after pressure ulcer classification system education. Conclusion: Overall understanding of pressure ulcer classification system and incontinence-associated dermatitis after pressure ulcer classification system education was increased, but tended to have lack of visual discrimination ability regarding stage III, suspected deep tissue injury. Differentiated continuing education based on clinical practice is needed to improve knowledge and visual discrimination ability for pressure ulcer classification system, and comparison experiment research is required to evaluate its effects.

• Physical Therapy Korea
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• v.30 no.2
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• pp.102-109
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• 2023

Background: While efforts have been made to differentiate fall risk in older adults using wearable devices and clinical methodologies, technologies are still infancy. We applied a decision tree (DT) algorithm using inertial measurement unit (IMU) sensor data and clinical measurements to generate high performance classification models of fall risk of older adults. Objects: This study aims to develop a classification model of fall risk using IMU data and clinical measurements in older adults. Methods: Twenty-six older adults were assessed and categorized into high and low fall risk groups. IMU sensor data were obtained while walking from each group, and features were extracted to be used for a DT algorithm with the Gini index (DT1) and the Entropy index (DT2), which generated classification models to differentiate high and low fall risk groups. Model's performance was compared and presented with accuracy, sensitivity, and specificity. Results: Accuracy, sensitivity and specificity were 77.8%, 80.0%, and 66.7%, respectively, for DT1; and 72.2%, 91.7%, and 33.3%, respectively, for DT2. Conclusion: Our results suggest that the fall risk classification using IMU sensor data obtained during gait has potentials to be developed for practical use. Different machine learning techniques involving larger data set should be warranted for future research and development.

• Tuberculosis and Respiratory Diseases
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• v.78 no.3
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• pp.180-189
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• 2015

Accurate lymph node staging of lung cancer is crucial in determining optimal treatment plans and predicting patient outcome. Currently used lymph node maps have been reconciled to the internationally accepted International Association for the Study of Lung Cancer (IASLC) map published in the seventh edition of TNM classification system of malignant tumours. This article provides computed tomographic illustrations of the IASLC nodal map, to facilitate its application in day-to-day clinical practice in order to increase the appropriate classification in lung cancer staging.

• The Journal of Korean Academy of Prosthodontics
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• v.44 no.2
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• pp.243-249
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• 2006

Statement of problem: It is important to have a correct presurgical treatment plan before any implant surgery. It must contain substantial information about the patient concerned. However, the standard classification only notifies the dentist about various structural, pathological and physiological dimensions Due to diverse structure of the jaw bone, current standard classification does not tell spatial dimensions of the available bone for implant insertion sites. Purpose of study: The purpose of this study is to report the establishment of the systematic implant treatment plan and its clinical treatment using $Implan^(R)$ program which is based on ASCIi-classification that is available for future diagnosis and scale of treatment and for systematic implant insertion. Results: By assisting the systemic measurement of the available alveolus dimension during implant surgery, it was easy to set initial implant treatment plan. Conclusion: Using $Implan^(R)$ program which is based on ASCIi-classification system that allows the establishment of systemic implant treatment plan and successful clinical performance, it was possible to establish the founding or initial implant treatment plan , the acquisition of information, and the systematization of documentation.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.49-56
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• 2011

It is urgently needed to develop programs supporting lifelong education for nurses and students of nursing, which are not restricted by time or space and use personal computers or smartphone. The purpose of this study is to develop CCC(Clinical Care Classification) System into a education program and provides guideline to support clinical tasks for students of nursing. Comparing the search times of the book guideline and the web guideline developed, this study found that it was over 3.5 times faster. And its error rate was over four times lower. This result shows that it can provide accurate intervention for patients since it approaches to intervention and evaluation guideline fast and precisely in the actual tasks of nursing.

• The Journal of Korean Medicine
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• v.21 no.4
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• pp.73-83
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• 2000

Objectives: One of the most important and difficult things in SaSang Constitution Medicine is to diagnose and classify constitution. So there have been a lot of methods and tools to diagnose and classify it. We have attempted to show the reliability and clinical application of the QSCC Ⅱ (Questionnaire for the Sasang Constitution Classification Ⅱ), comparing with our own clinical research. Methods: We surveyed information from QSCC Ⅱ and compared QSCC Ⅱ' s reliability with clinical research of 54 patients' constitution(men 24, women 30). Results: Taeeum-in is the most commonly reported constitution by clinical research, and the next is Soeum-in. Soyang-in is the most commonly reported constitution by QSCC Ⅱ and the next is Taeeum-in. In Taeeum-in and Soeum-in' s items of QSCC Ⅱ, these matched those of the clinical research. Soyang-in' s items of QSCC Ⅱ did not match. Conclusions: The efficiency of QSCC Ⅱ is higher than clinical research in Taeeum-in, Soeum-in. But lower than clinical research, Soyang-in and Taeyang-in have no reliability in QSCC Ⅱ. So Soyang-in and Taeyang-in require alternative complementary studies in the future.

• Korea Journal of Hospital Management
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• v.6 no.3
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• pp.148-166
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• 2001

The purpose of this study is to classify elderly patient in long-term care facilities using RUG(Resource Utilization Group)-III. It is designed by measuring patient medical characteristics and medical staff time. Elderly patients are classified into 7 categories by clinical(medical and behavioral) hierarchical typology of patients. Through the tertiary split, all 44 groups are formulated. This classification is explained by each patient resource(staff time) utilization level which is called CMI(Case-Mix Index). Major findings are as follows; 1. The objects in this study were classified into 35 groups out of 44 groups. The most frequent category is clinical complex category(CCC; 38.9%). And extensive service category(ESC; 18.8%), reduced physical function category(RPC; 13.1%), special rehabilitation category(SRC; 12.8%), and impaired cognitive category(ICC; 0.00%) are followed. 2. The mean of total CMI was $1.02{\pm}0.36$, ranging from 0.68 to 1.44(1 vs 2.12). The mean of CMI of SRC is only 1.17 which should be the highest. The means of ESC and see are equally 1.20. The means of CMI of CCI, ICC, BPC, and RPC were 0.90, 0.75, 0.83 and 0.96, respectively. 3. The validity of this classification was tested. Trend-test using Regression Analysis was done in the secondary split level. SCC, CCC, ICC, and RPC which covered 68.4% of this research objects showed linear trend of CMI in interim classification. This results were statistically significant. 4. In clinical hierarchy, the trend were showed linearity. But the multiple comparison of categories using Scheffe-test showed that SRC, ESC and see had same level of CMI means and CCC and ICC, too. This results were statistically significant. Classifying elderly patients with RUG-III, the results showed partly linear trend in clinical hierarchy and in interim classification in conclusion. But, in clinical hierarchy, it was failed to show the consistent order of CMI. It can be explained by two reasons. One is that this research subjects were overlapped in each clinical hierarchy group. And the other is that the some of the characteristics for clinical hierarchy is not appropriate for them. For the further study, it needs to have proper sample size and to modify RUG-III to K-RUG to consider our.. medical environment.

• Biomedical Science Letters
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• v.23 no.3
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• pp.223-229
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• 2017

Fungal infections by human pathogenic fungi are increasing globally in elderly, children and immune suppressed or deficient patients. Aspergillus fumigatus is one of the well-known pathogenic fungi and causes aspergilloses in human world widely. However, current identification and classification methods based on its phenotypic characteristics still have limitations. Therefore, currently, molecular biological tools using their DNA sequences are used for genotype identification and classification. In the present study, in order to analyze genetic variations of A. fumigatus clinical isolates, a total of six housekeeping genes were amplified by PCR using specific primer pairs and multi-locus sequence typing (MLST) assay. Results from phylogenetic tree analysis showed that most A. fumigatus strains (88.9%) from respiratory specimens were classified into cluster A and B, and approximately half of A. fumigatus strains (46%) from non-respiratory specimens were classified into cluster C and D. Although the sample size was limited, genetic characteristics of A. fumigatus clinical isolates according to their origins were very similar and well-correlated with other clinical data.