• Nuclear Engineering and Technology
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• 제55권1호
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• pp.100-108
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• 2023

In this study, a neural network model inspired by a one-dimensional convolution U-net is developed to automatically accelerate edge localized mode (ELM) detection from big diagnostic data of fusion devices and increase the detection accuracy regardless of the hyperparameter setting. This model recognizes the input signal patterns and overcomes the problems of existing detection algorithms, such as the prominence algorithm and those of differential methods with high sensitivity for the threshold and signal intensity. To train the model, 10 sets of discharge radiation data from the KSTAR are used and sliced into 11091 inputs of length 12 ms, of which 20% are used for validation. According to the receiver operating characteristic curves, our model shows a positive prediction rate and a true prediction rate of approximately 90% each, which is comparable to the best detection performance afforded by other algorithms using their optimized hyperparameters. The accurate and automatic ELM-burst detection methodology used in our model can be beneficial for determining plasma properties, such as the ELM frequency from big data measured in multiple experiments using machines from the KSTAR device and ITER. Additionally, it is applicable to feature detection in the time-series data of other engineering fields.

• Asian Pacific Journal of Cancer Prevention
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• 제17권9호
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• pp.4377-4380
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• 2016

Background: To compare diagnostic performance in differentiating benign from malignant ovarian masses between IOTA (the International Ovarian Tumor Analysis) simple rules and subjective sonographic assessment. Materials and Methods: Women scheduled for elective surgery because of ovarian masses were recruited into the study and underwent ultrasound examination within 24 hours of surgery to apply the IOTA simple rules by general gynecologists and to record video clips for subjective assessment by an experienced sonographer. The diagnostic performance of the IOTA rules and subjective assessment for differentiation between benign and malignant masses was compared. The gold standard diagnosis was pathological or operative findings. Results: A total of 150 ovarian masses were covered, comprising 105 (70%) benign and 45 (30%) malignant. Of them, the IOTA simple rules could be applied in 119 (79.3%) and were inconclusive in 31 (20.7%) whereas subjective assessment could be applied in all cases (100%). The sensitivity and the specificity of the IOTA simple rules and subjective assessment were not significantly different, 82.9% vs 86.7% and 94.0% vs 94.3% respectively. The agreement of the two methods in prediction was high with a Kappa index of 0.835. Conclusions: Both techniques had a high diagnostic performance in differentiation between benign and malignant ovarian masses but the IOTA rules had a relatively high rate of inconclusive results. The IOTA rules can be used as an effective screening technique by general gynecologists but when the results are inconclusive they should consult experienced sonographers.

• 대한소아치과학회지
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• 제28권1호
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• pp.16-24
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• 2001

레이저 형광법을 이용하여 각 개인의 우식의 활성도를 측정할 수 있는지를 규명하기 위해 $7\sim9$세의 아동 50명을 대상으로 치아의 순면과 협면에 아르곤 레이저를 조사하고 특수 필터를 사용하여 초기 치아우식증이 관찰되는 치아의 수를 측정하고, 이와 같은 초기 치아우식증의 수를 측정하는 우식활성법과 기존의 우식 활성도 측정 방법인 dDfFtT rate, Streptococcus mutans colony count와 상관성을 비교, 평가하고, 레이저 형광법을 이용한 우식활성검사의 특이도, 민감도, 진단력을 평가한 결과, 다음과 같은 결론을 얻었다. 1. 아르곤 레이저 형광법을 이용한 우식활성도 측정법은 기존의 Streptococcus mutans colony count 검사법과 비교적 높은 상관관계를 보였다($\gamma=0.48$, P<0.01). 2. 아르곤 레이저 형광법을 이용한 우식활성도 측정법은 dDfFtT rate 검사와 상관관계가 있었다($\gamma=0.39$, P<0.01). 3. Streptococcus mutans colony count와 dDfFtT rate와는 낮은 상관관계가 있었다($\gamma=0.27$, P<0.05). 4. dDfFtT rate를 기준검사 방법으로 하였을 때, 레이저 형광법을 이용한 우식활성 검사법은 특이도 44.4%, 민감도 85.7%, 진단력이 87.8%였다. 5. dDfFtT rate를 기준검사방법으로 하였을 때, Streptococcus mutans colony count는 특이도 77.8%, 민감도 92.9%, 진단력이 84.8%였다. 6. Streptococcus mutans colony count 검사법을 기준검사 방법으로 하였을 때 레이저 형광법을 이용한 우식활성 검사법은 특이도 40.0%, 민감도 84.8%, 진단력이 95.1%였다. 이를 종합해 볼 때 레이저 형광법을 이용하여 관찰한 우식활성 검사법은 기존의 우식활성검사 및 구강환경 검사와 비교적 높은 상관관계, 우수한 진단학적 지표를 보여 주므로써 향후 임상적으로 신뢰도와 타당성이 높은 우식활성 검사법으로서 그 활용 가능성이 높을 것으로 사료된다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권8호
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• pp.3097-3100
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• 2015

Projections of cancer cases are particularly useful in developing countries to plan and prioritize both diagnostic and treatment facilities. In the prediction of cancer cases for the future period say after 5 years or after 10 years, it is imperative to use the knowledge of past time trends in incidence rates as well as in population at risk. In most of the recently published studies the duration for which the time trend was assessed was more than 10 years while in few studies the duration was between 5-7 years. This raises the question as to what is the optimum time period which should be used for assessment of time trends and projections. Thus, the present paper explores the suitability of different time periods to predict the future rates so that the valid projections of cancer burden can be done for India. The cancer incidence data of selected cancer sites of Bangalore, Bhopal, Chennai, Delhi and Mumbai PBCR for the period of 1991-2009 was utilized. The three time periods were selected namely 1991-2005; 1996-2005, 1999-2005 to assess the time trends and projections. For the five selected sites, each for males and females and for each registry, the time trend was assessed and the linear regression equation was obtained to give prediction for the years 2006, 2007, 2008 and 2009. These predictions were compared with actual incidence data. The time period giving the least error in prediction was adjudged as the best. The result of the current analysis suggested that for projections of cancer cases, the 10 years duration data are most appropriate as compared to 7 year or 15 year incidence data.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Clinical and Experimental Pediatrics
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• 제59권3호
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• pp.139-144
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• 2016

Purpose: Acute pyelonephritis (APN) is a serious bacterial infection that can cause renal scarring in children. Early identification of APN is critical to improve treatment outcomes. The neutrophil-lymphocyte ratio (NLR) is a prognostic marker of many diseases, but it has not yet been established in urinary tract infection (UTI). The aim of this study was to determine whether NLR is a useful marker to predict APN or vesicoureteral reflux (VUR). Methods: We retrospectively evaluated 298 pediatric patients ($age{\leq}36months$) with febrile UTI from January 2010 to December 2014. Conventional infection markers (white blood cell [WBC] count, erythrocyte sedimentation rate [ESR], C-reactive protein [CRP]), and NLR were measured. Results: WBC, CRP, ESR, and NLR were higher in APN than in lower UTI (P<0.001). Multiple logistic regression analyses showed that NLR was a predictive factor for positive dimercaptosuccinic acid (DMSA) defects (P<0.001). The area under the receiver operating characteristic (ROC) curve was high for NLR (P<0.001) as well as CRP (P<0.001) for prediction of DMSA defects. NLR showed the highest area under the ROC curve for diagnosis of VUR (P<0.001). Conclusion: NLR can be used as a diagnostic marker of APN with DMSA defect, showing better results than those of conventional markers for VUR prediction.

• 한국환경과학회지
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• 제15권1호
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• pp.9-19
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• 2006

The purpose of this research is development of radar data assimilation observed at Jindo S-band radar The accurate observational data assimilation system is one of the important factors to meteorological numerical prediction of the region scale. Diagnostic analysis system LAPS(Local Analysis and Prediction System) developed by US FSL(Forecast Systems Laboratory) is adopted assimilation system of the Honam district forecasting system. The LAPS system was adjusted in calculation environment in the Honam district. And the improvement in the predictability by the application of the LAPS system was confirmed by the experiment applied to Honam district local severe rain case of generating 22 July 2003. The results are as follows: 1) Precipitation amounts of Gwangju is strong associated with the strong in lower level from analysis of aerological data. This indicated the circulation field especially, 850hPa layer, acts important role to precipitation in Homan area. 2) Wind in coastal area tends to be stronger than inland area and radar data show the strong wind in conversions zone around front. 3) Radar data assimilation make the precipitation area be extended and maximum amount of precipitation be smaller. 4) In respect to contribution rate of different height wind field on precipitation variation, radar data assimilation of upper level is smaller than that of lower level.

• 한국방사선학회논문지
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• 제10권6호
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• pp.443-450
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• 2016

본 연구는 복부 전산화단층촬영 영상을 이용하여 지방간환자의 영상을 질감특징분석과 ROC curve 분석을 하였으며, 컴퓨터보조진단시스템의 구현을 위한 실험적인 선형 연구로서 전산화단층촬영 영상에서 지방간의 객관적이고 신뢰성 있는 진단 정보를 의사에게 제공하고자 하였다. 실험은 정상 및 지방간 복부 전산화단층촬영 영상을 실험영상으로 하여 설정된 구역에 대한 wavelet 변환을 거쳐 질감의 특징값을 나타내는 6가지 파라미터로 통계적 분석 결과를 나타내었다. 그 결과 엔트로피, 평균밝기, 왜곡도는 90% 이상의 비교적 높은 인식률을 보였고, 대조도, 평탄도, 균일도는 약 70% 정도로 비교적 낮은 인식률을 나타내었다. ROC curve를 이용한 분석에서 6가지의 파라미터 모두 0.900(p=0.0001)이상을 나타내어 질환인식에 의미가 있는 결과를 나타내었다. 또한 6가지 파라미터에서 질환 예측을 위한 cut-off 값을 결정하였다. 이러한 결과는 향후 복부 전산화단층촬영 영상에서 질환 자동검출 및 최종진단의 예비 진단 자료로서 적용 가능할 것이다.

• Nuclear Medicine and Molecular Imaging
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• 제42권sup1호
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• pp.101-109
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• 2008

Cervix cancer is one of common gynecological cancers in the world, and staged with FIGO or TNM system. However, these clinical staging systems lack information about lymph node or distant metastases, thus imaging modalities are considered to make an appropriate therapeutic plan and enhance overall survival rate. In this context, FDG PET is recommended to pre-treatment stating and prognosis prediction, for it could noninvasively evaluate the status of lymph nodes, especially abdominal paraaortic nodes which are closely related with prognosis. Moreover, the degree of FDG uptake is correlated with prognosis. Although there is no consistent method for surveillance of cervix cancer, FDG PET seems a very important tool in detecting tumor recurrence because it is much more advantageous than conventional imaging modalities such as MRI for discerning recurrent tumor from fibrosis caused by radiation or surgery. Furthermore, FDG PET could be used to evaluate treatment response. On the other hand, recently introduced PET/CT is expected to play an ancillary role to FIGO staging by adding anatomical information, and enhance diagnostic performance of PET by decreasing false positive findings.

• Asian Pacific Journal of Cancer Prevention
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• 제17권4호
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• pp.2297-2299
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• 2016

Background: Early detection of malignant transformation with expression biomarkers has significant potential to improve the survival rate of patients as such biomarkers enable prediction of progression and assess sensitivity to chemotherapy. The expression of interferon inducible transmembrane protein 1 (IFITM1) has been associated with early invasion events in several carcinomas, including head and neck cancers, and hence has been proposed as a novel candidate biomarker. As the incidence of oral squamous cell carcinoma (OSCC) is highest in the Indian population, we sought to investigate: 1) the expression pattern of IFITM1 in OSCC tissue samples obtained from Indian patients of Dravidian origin; and 2) the possibility of using IFITM1 expression as a potential biomarker. Materials and Methods: Total RNA extracted from thirty eight OSCC biopsy samples was subjected to semi-quantitative RT-PCR with IFITM1 and GAPDH specific primers. Results: Of the thirty eight OSCC samples that were analyzed, IFITM1 overexpression was identified in fifteen (39%). Seven expressed a low level, while the remainder expressed high level of IFITM1. Conclusions: The overexpression of IFITM1 in OSCC samples indicates that IFITM1 may be explored for the possibility of use as a high confidence diagnostic biomarker in oral cancers. To the best of our knowledge, this is the first time that IFITM1 overexpression is being reported in Indian OSCC samples.