• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.10
• /
• pp.4323-4328
• /
• 2015

Background: Breast cancer is the most common cause of deaths of cancer in women. Nowadays, following completion of imaging methods, mainly fine needle aspiration biopsy (FNAB) and core biopsy methods have been used for establishing cytopathological diagnosis although discussions regarding superiority continue. Materials and Methods: Those with a complaint of "mass in breast" along with those diagnosed to have a mass as a result of routine physical examination among all patients applying to our clinic between 01.01.2009 and 31.12.2011 were retrospectively assessed. Totals of 146 and 64 patients with complete radiological observation who had undergone FNAB and core biopsies, respectively, were evaluated. Postoperative pathological results of patients of both groups receiving surgery were also taken into consideration. All results were compared in terms of false positivity/negativity, sensitivity/specifity, surgery types and distribution of postoperative results with regard to diagnoses along with those of malignant/benign masses with regard to quadrants determined. Results: Diagnostic malignancy power of mammographic BIRADS classification was 87.3%. However, the value was 75% in the core biopsy group. Sensitivity and specifity following comparison of FNAB and postoperative pathology results of those receiving surgery were 85.4% and 92.9% while they were 93.5% and 100% in the core biopsy group. Diagnostic malignancy power, calculated by determining AUC in ROC analysis, of FNAB was 89.1% while that of core biopsy was 96.7%. Conclusions: It was shown that core biopsy is superior to FNAB in terms of sensitivity, specificity and accurate histopathological classification. However; quick, cheap and basic diagnosis by means of FNAB should not be ignored. Sensitivity of FNAB is rather high in experienced hands and furthermore it would be expected to be lower than with core biopsy.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
• /
• v.28 no.2
• /
• pp.106-111
• /
• 2017

Background and Objectives : The purpose of this study was to investigate the criterion-related concurrent validity of two standardized auditory-perceptual assessments and the Acoustic Voice Quality Index (AVQI) for measuring dysphonia severity in patients with vocal cord paralysis (VCP). Materials and Methods : Total 210 patients with VCP and 236 normal voice subjects were asked to sustain the vowel [a:] and to read aloud the Korean text "Walk". A 2 second mid-vowel portion of the sustained vowel and two sentences (with 26 syllables) were recorded. And then voice samples were edited, concatenated, and analyzed according to Praat script. Two standardized auditory-perceptual assessment (GRBAS and CAPE-V) were performed by three raters. Results : The VCP group showed higher AVQI, Grade (G) and Overall Severity (OS) values than normal voice group. And the correlation among AVQI, G, and OS ranged from 0.904 to 0.926. In ROC curve analysis, cutoff values of AVQI, G, and OS were <3.79, <0.00, and <30.00, respectively, and the AUC of each analysis was over .89. Conclusion : AVQI and auditory evaluation can improve the early screening ability of VCP voice and help to establish effective diagnosis and treatment plan for VCP-related dysphonia.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.5179-5196
• /
• 2019

To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.

• Journal of Korean Clinical Nursing Research
• /
• v.26 no.2
• /
• pp.265-273
• /
• 2020

Purpose: The purpose of this study was to test the predictive validity of the Fall Assessment Scale-Korean version (FAS-K) and to find the most appropriate cutoff score to screen high-risk fall groups in adult patients in general hospitals in Korea. Methods: We performed a prospective evaluation study in medical and surgical ward patients at two major general hospitals in Seoul. Data were collected from Nov. 1, 2018 to Feb. 28, 2019, nurses performed 651 observation series. The researcher measured the fall risk assessment score by applying FAS-K, MFS (Morse Fall Scale), and JHFRAT (Johns Hopkins Hospital Fall Risk Assessment tool) to the patients twice a week between 10 am and 12 noon. Data were analyzed using Pearson's corelation coefficients, and the sensitivity, specificity, predictive value, and the area under the curve (AUC) of the three tools. Results: The FAS-K was positively correlated with the MFS (r=.70, p<.001) and the JHFRAT (r=.82, p<.001). According to the receiver operating characteristics (ROC) curve analysis of the FAS-K, sensitivity, specificity, and positive and negative prediction values were 85.3%, 49.4%, 8.5%, and 98.4%, respectively, when the FAS-K score was 4. Therefore, the cut-off score of the FAS-K to identify groups with high fall risk was 4. Conclusion: The FAS-K is a valid tool for measuring fall risk in adult inpatients. In addition, the FAS-K score, 4, can be used to identify high-risk fall groups and know specific points in time to provide active interventions to prevent falls.

• Tuberculosis and Respiratory Diseases
• /
• v.67 no.5
• /
• pp.430-435
• /
• 2009

Background: Thus far, research studies on community-acquired pneumonia (CAP) have focused on its clinical severity. Recently, it has been determined that procalcitonin (PCT) level is correlated with severity of CAP. A retrospective study conducted at our hospital used risk predictability and PCT to determine whether or no PCT is useful in assessing the severity of CAP. Methods: This study covered 92 CAP cases that were admitted to the respiratory department at Changwon Fatima Hospital between July 1, 2008 and June 30, 2009. All enrolled subjects were measured for infection markers and risk predictability. Results: Based on hospital admission data, enrolled subjects had Pneumonia Severity Index (PSI) scores serving as risk predictors showed that both PCT and white blood cell (WBC) were statistically significant as infection markers (p=0.001, 0.037). Thus, this study used ROC curves in PSI for data analysis. As a result, it was determined that the area under curve (AUC) of PCT and WBC was 0.694 and 0.593 respectively, indicating that PCT has a higher test value for WBC, when PCT was higher than 0.745 ng/mL. In addition, it was found that PCT levels higher than 0.745 ng/mL had higher PSI scores than the group with PCT lower than 0.745 ng/mL (p=0.032). Conclusion: In order to predict risk of pneumonia cases admitted due to symptoms of CAP, it is important to consider PCT as well as PSI, and follow-up monitoring of PCT cases.

• Tuberculosis and Respiratory Diseases
• /
• v.69 no.6
• /
• pp.450-455
• /
• 2010

Background: High cortisol levels are frequently observed in patients with severe infections are of prognostic value in sepsis. The aim of this study was to evaluate the clinical usefulness of serum cortisol in assessment for the severity of community-acquired pneumonia (CAP). Methods: This study analyzed the results of 52 CAP subjects admitted in Changwon Fatima Hospital between July 2008 to May 2010. Total serum cortisol, infection markers such as C-reactive protein (CRP), procalcitonin (PCT) and CURB (Confusion, Uremia, Respiratory rate, Blood pressure)-65 were examined retrospectively. Results: In clinically unstable subjects on admission day 4, baseline serum cortisol, CURB-65, and CRP were elevated significantly compared to those of stable subjects. Area under curve (AUC) of cortisol, CRP, and CURB-65 from ROC curves were 0.847, 0.783, and 0.724 respectively. In the subjects with serum cortisol ${\geq}22.82{\mu}g/dL$, CRP, PCT, CURB-65 score, and mortality were significantly elevated. Conclusion: These findings suggest that measurement of serum cortisol in early stage may provide helpful information in the assessment of CAP severity.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.34 no.3
• /
• pp.142-148
• /
• 2020

The purpose of this study was to evaluate the validity of Deficiency and Excess Pattern Identification Questionnaire. The number of subjects enrolled in this study was 431. Pearson Correlation Coefficient analysis were conducted to reveal the correlation among Deficiency and Excess Pattern Identification Questionnaire, Grip Strength and Quality of life. ROC-curve analysis were used to suggest optimal cut off value. Cohen Kappa also used to analyze for diagnostic validity. The significant p-value was < .05. The Deficiency questionnaire had positive correlation with the score of the expert and negative correlation with Grip Strength and Quality of life (p<.001). The Excess questionnaire had positive correlation with the score of the expert and negative correlation with Quality of life (p<.001). The optimal cut off value was 56.5 to separate deficiency and non deficiency and 47.5 to separate excess and non-excess. Furthermore, AUC was .900 and .851 accordingly. Cohen Kappa value between deficiency questionnaire and the expert was .640. Cohen Kappa value between excess questionnaire and the expert was .513. This study reveals that Deficiency and Excess Pattern Identification Questionnaire is valid. However, further study considering of gender, age, and health condition and so on, is needed.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.23 no.6
• /
• pp.125-135
• /
• 2020

The uncontrolled urban expansion causes various social, economic problems and natural/environmental problems. Therefore, it is necessary to forecast urban expansion by identifying various factors related to urban expansion. This study aims to forecast it using a decision tree that is widely used in various areas. The study used geographic data such as the area of use, geographical data like elevation and slope, the environmental conservation value assessment map, and population density data for 2006 and 2018. It extracted the new urban expansion areas by comparing the residential, industrial, and commercial zones of the zoning in 2006 and 2018 and derived a decision tree using the 2006 data as independent variables. It is intended to forecast urban expansion in 2030 by applying the data for 2018 to the derived decision tree. The analysis result confirmed that the distance from the green area, the elevation, the grade of the environmental conservation value assessment map, and the distance from the industrial area were important factors in forecasting the urban area expansion. The AUC of 0.95051 showed excellent explanatory power in the ROC analysis performed to verify the accuracy. However, the forecast of the urban area expansion for 2018 using the decision tree was 15,459.98㎢, which was significantly different from the actual urban area of 4,144.93㎢ for 2018. Since many regions use decision tree to forecast urban expansion, they can be useful for identifying which factors affect urban expansion, although they are not suitable for forecasting the expansion of urban region in detail. Identifying such important factors for urban expansion is expected to provide information that can be used in future land, urban, and environmental planning.

• The Journal of Internal Korean Medicine
• /
• v.41 no.6
• /
• pp.1015-1029
• /
• 2020

Purpose: This study assessed the validity of a questionnaire (SEID-Q27) for diagnosis of chronic fatigue syndrome (CFS), designed based on the systematic exertion intolerance disorder (SEID) criteria. Methods: Two groups of participants were recruited: 1. a non-CFS control group: adult university personnel with a Chalder fatigue scale (CFQ) score ≥15, and 2. a CFS patient group: patients from an online CFS community diagnosed with CFS (diagnostic code of G93.3) with the symptoms present. The survey ran from September to October, 2020. The validity of the questionnaire was investigated by factor analysis and receiver operator characteristic (ROC) analysis. Results: Among the 35 adults surveyed, 30 (86%) participants had CFQ scores ≥15 (15 males and 15 females) and 5 (14%) had a CFS diagnosis (2 males and 3 females). The total mean score was significantly different between the two groups (CFS: 6.8±2.2 vs. control: 4.4±2.4, p<0.05). The area under the curve (AUC) was 0.827. With a cut-off point 62, the sensitivity was 60%, specificity 97%, and the discriminant ability of the survey was 79%. Conclusions: The SEID -Q27 appears to be a useful instrument for the diagnosis of CFS using SEID criteria. However, further large-scale studies are needed with greater numbers of participants.

• Food Science of Animal Resources
• /
• v.41 no.2
• /
• pp.312-323
• /
• 2021

The purpose of this study was to use 1H nuclear magnetic resonance (1H NMR) to quantify taste-active and bioactive compounds in chicken breasts and thighs from Korean native chicken (KNC) [newly developed KNCs (KNC-A, -C, and -D) and commercial KNC-H] and white-semi broiler (WSB) used in Samgye. Further, each breed was differentiated using multivariate analyses, including a machine learning algorithm designed to use metabolic information from each type of chicken obtained using 1H-13C heteronuclear single quantum coherence (2D NMR). Breast meat from KNC-D chickens were superior to those of conventional KNC-H and WSB chickens in terms of both taste-active and bioactive compounds. In the multivariate analysis, meat portions (breast and thigh) and chicken breeds (KNCs and WSB) could be clearly distinguished based on the outcomes of the principal component analysis and partial least square-discriminant analysis (R2=0.945; Q2=0.901). Based on this, we determined the receiver operating characteristic (ROC) curve for each of these components. AUC analysis identified 10 features which could be consistently applied to distinguish between all KNCs and WSB chickens in both breast (0.988) and thigh (1.000) meat without error. Here, both 1H NMR and 2D NMR could successfully quantify various target metabolites which could be used to distinguish between different chicken breeds based on their metabolic profile.