• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.569-572
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• 2008

The possibility to extent the solution in human detection problem for plug-in on vision-based Human Computer Interaction domain is very attractive, since the successful of the machine leaning theory and computer vision marriage. Bayesian logistic regression is a powerful classifier performing sparseness and high accuracy. The difficulties of finding people in an image will be conquered by implementing this Bavesian model as classifier. The comparison with other massive classifier e.g. SVM and RVM will introduce acceptance of this method for human detection problem. Our experimental results show the good performance of Bavesian logistic regression in human detection problem, both in trade-off curves (ROC, DET) and real-implementation compare to SVM and RVM.

• Korean Journal of Radiology
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• 제23권6호
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• pp.664-673
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• 2022

Objective: To evaluate the performance of baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping of the extraocular muscles (EOMs) in the prediction of treatment response to intravenous glucocorticoid (IVGC) therapy for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO) and to investigate the effect of fat-suppression (FS) in T2 mapping in this prediction. Materials and Methods: A total of 79 patients clinically diagnosed with active, moderate-to-severe TAO (47 female, 32 male; mean age ± standard deviation, 46.1 ± 10 years), including 43 patients with a total of 86 orbits in the responsive group and 36 patients with a total of 72 orbits in the unresponsive group, were enrolled. Baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping with FS (i.e., FS T2 mapping) or without FS (i.e., conventional T2 mapping) of EOMs were compared between the two groups. Independent predictors of treatment response to IVGC were identified using multivariable analysis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the prediction models. Differences between the models were examined using the DeLong test. Results: Compared to the unresponsive group, the responsive group had a shorter disease duration, lower kurtosis (FS-kurtosis), lower standard deviation, larger 75th, 90th, and 95th (FS-95th) T2 relaxation times in FS mapping and lower kurtosis in conventional T2 mapping. Multivariable analysis revealed that disease duration, FS-95th percentile, and FS-kurtosis were independent predictors of treatment response. The combined model, integrating all identified predictors, had an optimized area under the ROC curve of 0.797, 88.4% sensitivity, and 62.5% specificity, which were significantly superior to those of the imaging model (p = 0.013). Conclusion: An integrated combination of disease duration, FS-95th percentile, and FS-kurtosis was a potential predictor of treatment response to IVGC in patients with active and moderate-to-severe TAO. FS T2 mapping was superior to conventional T2 mapping in terms of prediction.

• Asian Pacific Journal of Cancer Prevention
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• 제15권19호
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• pp.8447-8450
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• 2014

Background: To evaluate factors for predicting the granulosa cell tumor of the ovary (GCTO) pre-operatively. Materials and Methods: This retrospective designed study was conducted on 34 women with GCTO as the study group and 76 women with benign ovarian cysts as the control group. Data were recorded from the hospital database and included age, body mass index (BMI), parity, serum estradiol ($E_2$) levels, diameter of the mass, ultrasonographic features, serum CA125 level, risk of malignancy index (RMI), duration of menopause, postoperative histopathology result, and the neutrophil/lymphocyte ratio (NLR). Results: The demographic parameters showed no statistically significant difference between the groups. Preoperative diameter of the mass, CA125, duration of menopause, and neutrophil/lymphocyte ratio were significantly different between the groups. ROC curve analysis demonstrated that diameter of the mass, serum estradiol and Ca125 levels, RMI and NLR may be discriminative factors in predicting GCTO preoperatively. Conclusions: In conclusion, we think that a careful preoperative workshop including diameter of the mass, serum estradiol ($E_2$) and Ca125 levels, RMI and NLR may predict GCTO and may prevent incomplete approaches.

• International Journal of Advanced Culture Technology
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• 제7권1호
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• pp.8-13
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• 2019

Despite technical advances in healthcare, the rates of hospital-acquired pressure injury (HAPI) are still high although many are potentially preventable. The purpose of this study was to determine whether tree-based prediction modeling is suitable for assessing the risk of HAPI in ICU patients. Retrospective cohort study has been carried out. A decision tree model was constructed with Age, Weight, eTube, diabetes, Braden score, Isolation, and Number of comorbid conditions as decision nodes. We used RStudio for model training and testing. Correct prediction rate of the final prediction model was 92.4 and the Area Under the ROC curve (AUC) was 0.699, which means there is about 70% chance that the model is able to distinguish between HAPI and non-HAPI. The results of this study has limited generalizability as the data were from a single academic institution. Our research finding shows that the data-driven tree-based prediction modeling may potentially support ICU sensitive risk assessment for HAPI prevention.

• Geomechanics and Engineering
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• 제36권5호
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• pp.441-453
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• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권5호
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• pp.345-349
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• 2009

소결 북마킹(social bookmarking) 시스템은 사용자가 북마크를 저장하고 공유할 수 있는 플랫폼을 제공하는 웹 기반(web-based) 시스템으로 폭소노미(folksonomy)를 이용한 대표적인 웹2.0 서비스이다. 소셜 북마킹 시스템에서의 스패머(spammer)란 자신들의 이익을 위해서 시스템을 고의적으로 악용하는 사람을 말한다. 스패머는 많은 양의 잘못된 정보를 시스템에 포스팅(posting)하기 때문에 전체 소셜 북마킹 시스템의 리소스(resource)를 쓸모없게 만들어 버린다. 따라서, 스패머를 빠른 시간 안에 탐지하고 그들의 접근을 차단하는 것은 시스템의 붕괴를 방지하기 위해 중요하다. 본 논문에서는 사용자가 사용한 태그에 대한 데이터를 추출하여, 사용자가 스패머 인지 아닌지를 예측하는 모델을 기계학습의 다양한 방법을 적용하여 생성한 후 그 성능을 비교해 보았다. 구체적으로, 결정테이블 (decision table, DT), 결정트리(decision tree, ID3), 나이브 베이즈 분류기($na{\ddot{i}}ve$ Bayes classifier), TAN(tree-augmented $na{\ddot{i}}ve$ Bayes) 분류기, 인공신경망(artificial neural network)의 방법을 비교하였다. 그 결과 AUC(area under the ROC curve)와 모델 생성시간을 고려하였을 때 나이브 베이즈 분류기가 가장 만족할 만한 성능을 보였다. 나이브 베이즈 분류기의 분류 결과가 가장 좋았던 이유는 성능을 비교하는 데 사용된 AUC가 결정트리 계열의 방법(ID3 등)보다 나이브 베이즈 분류기에서 일반적으로 높게 나오는 경향이 있다는 것과, 스패머 탐지 문제가 선형으로 분리 가능한 경우(lineally separable)와 유사할 가능성이 높기 때문으로 여겨진다.

• 생물정신의학
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• 제23권1호
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• pp.29-36
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• 2016

Objectives Firefighters and rescue workers are likely to be exposed to a variety of traumatic events; as such, they are vulnerable to the risk of post-traumatic stress disorder (PTSD). The psychometric properties of the Korean version of the PTSD Checklist (PCL), a widely used self-report screening tool for PTSD, were assessed in South Korean firefighters and rescue workers. Methods Data were collected via self-report questionnaires and semi-structured clinical interviews administered to 221 firefighters. Internal consistency, item-total correlation, one-week test-retest reliability, convergent validity, and divergent validity were examined. Content validity of the PCL was evaluated using factor analysis and receiver operating characteristic (ROC) analyses were used to estimate the optimal cutoff point and area under the curve. Results The PCL demonstrated excellent internal consistency (${\alpha}=0.97$), item-total correlation (r = 0.72-0.88), test-retest reliability (r = 0.95), and convergent and divergent validity. The total score of PCL was positively correlated with the number of traumatic events experienced (p < 0.001). Factor analysis revealed two theoretically congruent factors: re-experience/avoidance and numbing/hyperarousal. The optimal cutoff was 45 and the area under the ROC curve was 0.97. Conclusions The Korean version of the PCL may be a useful PTSD screening instrument for firefighters and rescue workers, further maximizing opportunities for accurate PTSD diagnosis and treatment.

• The Korean Journal of Pain
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• 제36권1호
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• pp.113-127
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• 2023

Background: Resting-state functional connectivity (rs-FC) may aid in understanding the link between painmodulating brain regions and the descending pain modulatory system (DPMS) in fibromyalgia (FM). This study investigated whether the differences in rs-FC of the primary somatosensory cortex in responders and non-responders to the conditioned pain modulation test (CPM-test) are related to pain, sleep quality, central sensitization, and the impact of FM on quality of life. Methods: This cross-sectional study included 33 females with FM. rs-FC was assessed by functional magnetic resonance imaging. Change in the numerical pain scale during the CPM-test assessed the DPMS function. Subjects were classified either as non-responders (i.e., DPMS dysfunction, n = 13) or responders (n = 20) to CPM-test. A generalized linear model (GLM) and a receiver operating characteristic (ROC) curve analysis were performed to check the accuracy of the rs-FC to differentiate each group. Results: Non-responders showed a decreased rs-FC between the left somatosensory cortex (S1) and the periaqueductal gray (PAG) (P < 0.001). The GLM analysis revealed that the S1-PAG rs-FC in the left-brain hemisphere was positively correlated with a central sensitization symptom and negatively correlated with sleep quality and pain scores. ROC curve analysis showed that left S1-PAG rs-FC offers a sensitivity and specificity of 85% or higher (area under the curve, 0.78, 95% confidence interval, 0.63-0.94) to discriminate who does/does not respond to the CPM-test. Conclusions: These results support using the rs-FC patterns in the left S1-PAG as a marker for predicting CPM-test response, which may aid in treatment individualization in FM patients.

• Clinical and Experimental Reproductive Medicine
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• 제37권2호
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• pp.115-124
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• 2010

목 적: 임신 전 $CD3^-/CD56^+/CD16^+$ 말초혈액 자연살해세포 (pbNK cell)의 분획과 세포용해 활성도를 정상군과 습관성 유산의 기왕력을 가진 환자군으로 나누어 비교, 분석하고 습관성 유산의 위험도를 제시할 수 있는 각각의 cut-off value를 설정하고자 하였다. 연구방법: 전향적 연구로서 습관성 유산의 기왕력이 있는 여성을 환자군 (n=35)으로 하였으며, 대조군으로 불임이나 습관성 유산의 기왕력이 없으며 정상아의 출산 경험이 있는 여성을 대조군 (n=15)으로 설정하였다. 유세포분석기를 이용하여 pbNK cell 분획 및 세포용해 활성도를 측정 후 그 결과를 비교 분석하였다. 결 과: pbNK cells의 분획은 습관성 유산 환자군에서 대조군에 비해 통계적으로 유의하게 높은 결과를 보였다($14.2{\pm}5.2$ vs. $9.4{\pm}3.7%$, p=0.002, 95% confidence interval [CI] 1.8~7.8). Receiver operating characteristic curve (ROC) 곡선을 이용하여 pbNK cell의 분획에 대한 cut-off values을 12.1%로 정하였을 때 습관성 유산의 위험도는 8.4배 증가하였다. pbNK cell의 K562 세포용해 활성도를 3가지 다른 Effector to Target (E:T) 비율 (50:1, 25:1, 12.5:1)을 사용하여 측정한 결과 각각의 경우에 있어 습관성 유산 환자군에서 대조군에 비해 통계적으로 유의하게 증가된 결과를 보였다 ($48.3{\pm}19.0$ vs. $31.3{\pm}11.9%$ in 50:1 ratio, p=0.002; $37.0{\pm}18.1$ vs. $20.2{\pm}9.2%$ in 25:1 ratio, p<0.001; $23.5{\pm}12.7$ vs. $12.4{\pm}7.3%$ in 12.5:1 ratio, p=0.001). ROC 곡선을 이용하여 각각 E:T 비율에서 세포용해 활성도의 cut-off values (43.1% in 50:1, 26.9% in 25:1, and 17.4% in 12.5:1)을 설정하여 분석한 결과 습관성 유산의 위험도는 각각 10.0배, 11.4배, 그리고 15.0배 증가된 결과를 보였다. 결 론: 원인이 분명하지 않은 습관성 유산 환자에서 pbNK cell의 분획과 세포용해 활성도를 측정하는 것은 면역학적 원인, 특히 동종면역 요인에 의한 습관성 유산의 유용한 진단 지표로 이용될 수 있을 것으로 사료된다. 향후 동종 면역반응에 의한 습관성 유산 환자에서 면역학적 원인의 치료 전, 후 pbNK cell의 분획과 세포용해 활성도를 측정, 비교하여 그 효과를 증명하는 연구가 필요할 것으로 생각된다.

• 대기
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• 제25권2호
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• pp.271-281
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• 2015

The objectives of this study are to develop a hydrological drought outlook system using GloSea5 (Global Seasonal forecasting system 5) which has recently been used by KMA (Korea Meteorological Association) and to evaluate the forecasting capability. For drought analysis, the bilinear interpolation method was applied to spatially downscale the low-resolution outputs of GloSea5 and PR (Predicted Runoff) was produced for different lead times (i.e., 1-, 2-, 3-month) running LSM (Land Surface Model). The behavior of PR anomaly was similar to that of HR (Historical Runoff) and the estimated values were negative up to lead times of 1- and 2-month. For the evaluation of drought outlook, SRI (Standardized Runoff Index) was selected and PR_SRI estimated using PR. ROC score was 0.83, 0.71, 0.60 for 1-, 2- and 3-month lead times, respectively. It also showed the hit rate is high and false alarm rate is low as shorter lead time. The temporal Correlation Coefficient (CC) was 0.82, 0.60, 0.31 and Root Mean Square Error (RMSE) was 0.52, 0.86, 1.20 for 1-, 2-, 3-month lead time, respectively. The accuracy of PR_SRI was high up to 1- and 2-month lead time on local regions except the Gyeonggi and Gangwon province. It can be concluded that GloSea5 has high applicability for hydrological drought outlook.