• Title/Summary/Keyword: Predictive Analysis

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Hypothesis Proposal about Predictive Factors and Optimal Age for Response to Herbal Medicine Treatment for Height Gain in Children: a Retrospective Review

  • Leem, Jungtae;Kim, Jeeyeun;Suh, Kyeungsuk;Lim, Youngkwern;Lee, Junhee
    • The Journal of Korean Medicine
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    • v.39 no.4
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    • pp.16-29
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    • 2018
  • Introduction: We aimed to investigate the predictive factors and optimal age for response to herbal medicine treatment for height gain in children. Methods: This retrospective chart review included 61 children (age range, 5-16 years) treated for height gain between 2011 and 2015. A predictive model was established by multiple linear regression analysis. Dependent variables were defined by the differences in percentile before and after herbal medicine treatment. The optimal cutoff value of patient age was determined by receiver operating curve analysis. Results : The age of initiation of herbal medicine therapy (p = 0.012) and administration of Forsythiae fructus (p = 0.002) were significant variables for treatment response. The adjusted R2 value was 0.231. The mean ages of the responder and non-responder groups were significantly different (p = 0.023). The optimal cutoff value of age for predicting treatment response was 9.75 years. Treatment response was better among children below 9.75 years of age. Conclusions: Patient age and administration of Forsythiae fructus were identified as determinants of response to herbal medicine treatment. Treatment of rhinitis and initiation of height gain treatment at an early age are critical for better response. These findings will provide fundamental data for further research.

Predictive capability of fasting-state glucose and insulin measurements for abnormal glucose tolerance in women with polycystic ovary syndrome

  • Chun, Sungwook
    • Clinical and Experimental Reproductive Medicine
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    • v.48 no.2
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    • pp.156-162
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    • 2021
  • Objective: The aim of the present study was to evaluate the predictive capability of fasting-state measurements of glucose and insulin levels alone for abnormal glucose tolerance in women with polycystic ovary syndrome (PCOS). Methods: In total, 153 Korean women with PCOS were included in this study. The correlations between the 2-hour postload glucose (2-hr PG) level during the 75-g oral glucose tolerance test (OGTT) and other parameters were evaluated using Pearson correlation coefficients and linear regression analysis. The predictive accuracy of fasting glucose and insulin levels and other fasting-state indices for assessing insulin sensitivity derived from glucose and insulin levels for abnormal glucose tolerance was evaluated using receiver operating characteristic (ROC) curve analysis. Results: Significant correlations were observed between the 2-hr PG level and most fasting-state parameters in women with PCOS. However, the area under the ROC curve values for each fasting-state parameter for predicting abnormal glucose tolerance were all between 0.5 and 0.7 in the study participants, which falls into the "less accurate" category for prediction. Conclusion: Fasting-state measurements of glucose and insulin alone are not enough to predict abnormal glucose tolerance in women with PCOS. A standard OGTT is needed to screen for impaired glucose tolerance and type 2 diabetes mellitus in women with PCOS.

Throughput Prediction of Pohang Port using Time Series Data: Application of SARIMA, Prophet and Neural Prophet (시계열 데이터를 활용한 포항항 물동량 예측: SARIMA, Prophet, Neural Prophet의 적용)

  • Jin-Ho Oh;Jeong-Won Choi;Tae-Hyun Kang;Young-Joon Seo;Dong-Wook Kwak
    • Korea Trade Review
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    • v.47 no.6
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    • pp.291-305
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    • 2022
  • In this study, the volume of Pohang Port was predicted. All cargo of Pohang port, iron ore, steel, and bituminous coals were selected as prediction targets. SARIMA, Prophet, and Neural Prophet were used as analysis methods. The predictive power of each model was verified, and a predictive model with high performance was used to predict the volume of goods in Pohang port. As a result of the analysis, it was found that Neural Prophet showed the highest performance in all predictive power. As a result of predicting the future volume of goods until August 2027 using Neural Prophet, it was found that the volume of all items in Pohang port was decreasing. In particular, it was analyzed that the decline in steel cargo was steep. In order to increase the volume of cargo at Pohang port, it is necessary to diversify the cargo handled at Pohang port and check the policy of increasing the volume of cargo.

Predictive V16alue of Thymidylate Synthase Expression in Gastric Cancer: A Systematic Review with Meta-analysis

  • Hu, Hua-Bin;Kuang, Lei;Zeng, Xiao-Min;Li, Bin;Liu, En-Yi;Zhong, Mei-Zuo
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.1
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    • pp.261-267
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    • 2012
  • Purpose: The relationship between thymidylate synthase (TS) expression and outcomes in gastric cancer (GC) patients remains controversial, although most studies reported poor survival and reduced response to fluoropyrimidine were related to high TS in tumors. We carried out a systematic review of the literature with meta-analysis to estimate the predictive value of TS expression from published studies. Methods: We indentified 24 studies analysing the outcome data in gastric cancer stratified by TS expression. Effect measures of outcome were hazard ratios (HRs) for overall survival (OS) and event-free survival (EFS), or the odds ratio (OR) for overall response rate (ORR). HRs and ORs from these eligible studies were pooled using random-effects meta-analysis. Results: Fifteen studies investigated outcomes in a total of 844 patients with advanced GC, and nine studies investigated outcomes in a total of 1,235 patients with localized GC undergoing adjuvant therapy. Meta-analysis of estimates showed high TS expression was significantly associated with poor OS in the advanced setting (HR: 1.43, 95%CI: 1.08 - 1.90), and poor EFS in the adjuvant setting (HR: 1.53, 95%CI: 1.01 - 2.32). Subgroup analysis demonstrated TS expression to haves even greater value in predicting OS, EFS and ORR in advanced GC patients treated with fluoropyrimidine monotherapy (HR for OS: 2.32, 95%CI: 1.53 - 3.50; HR for EFS: 1.76, 95%CI: 1.19 - 2.60; OR for ORR: 0.32, 95%CI: 0.11 - 0.95). Conclusion: High levels of TS expression were asssociated with a poorer OS for advanced GC patients compared with low levels. In the adjuvant setting, high TS expression was also associated with a worse EFS. Additional studies with consistent methodology are needed to define the precise predictive value of TS.

Multiple Regression Technique for Productivity Analysis of the Jointed Plane Concrete Pavement (JPCP)

  • Yoo, Wi-Sung
    • Korean Journal of Construction Engineering and Management
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    • v.9 no.6
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    • pp.268-276
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    • 2008
  • In highway construction projects, concrete pavement productivity has been challenged with constructors and decision-makers; at present there are few methods available to accurately evaluate the factors impacting on it. Any inefficient method to analyze it leads to the excessive schedule, higher rehabilitation costs, shorter service life, and reduction of ride quality. To implement these negative outcomes, constructors or decision-makers need a systematic tool that can be used to categorize the factors related to construction productivity. This paper applies multiple regression technique for productivity analysis of the Jointed Plane Concrete Pavement (JPCP), identifies the significant factors, and provides a predictive model assisting in monitoring and managing the productivity of the JPCP construction process. The completed and progressive projects are employed to derive and assess the proposed model. The results are analyzed to illustrate its capabilities.

Audio Watermarking Using Independent Component Analysis

  • Seok, Jong-Won
    • Journal of information and communication convergence engineering
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    • v.10 no.2
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    • pp.175-180
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    • 2012
  • This paper presents a blind watermark detection scheme for an additive watermark embedding model. The proposed estimation-correlation-based watermark detector first estimates the embedded watermark by exploiting non-Gaussian of the real-world audio signal and the mutual independence between the host-signal and the embedded watermark and then a correlation-based detector is used to determine the presence or the absence of the watermark. For watermark estimation, blind source separation (BSS) based on independent component analysis (ICA) is used. Low watermark-to-signal ratio (WSR) is one of the limitations of blind detection with the additive embedding model. The proposed detector uses two-stage processing to improve the WSR at the blind detector; the first stage removes the audio spectrum from the watermarked audio signal using linear predictive (LP) filtering and the second stage uses the resulting residue from the LP filtering stage to estimate the embedded watermark using BSS based on ICA. Simulation results show that the proposed detector performs significantly better than existing estimation-correlationbased detection schemes.

A Study on the Prediction of Void Closure in the Cogging Process of a Large Round Bar (대형 단조품 환봉 코깅 공정의 기공 압착 거동 예측에 관한 연구)

  • Song, M.C.;Kwon, I.K.;Park, Y.G.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2008.05a
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    • pp.75-78
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    • 2008
  • The predictive equation of void-closure was developed to evaluate void crush ratio with respect to the process variables in the cogging process of a large round bar. The comprehensive finite element analysis with the process variables such as reduction ratio and die width ratio was carried out. The predictive equation of void-closure for cogging process was established on the basis of the regression analysis with the extensive FE analysis results and verified by comparing the predicted results with FEA results with various forging passes.

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Validation of the Short Form Bobath Memorial Hospital Fall Risk Assessment Scale at a Specialized Geriatric Hospital in Korea (단축형 노인 낙상위험 사정도구의 타당도)

  • Sohng, Kyeong-Yae;Park, Mi Hwa;Chaung, Seung Kyo;Park, Hye Ja
    • Journal of Korean Public Health Nursing
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    • v.28 no.3
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    • pp.495-508
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    • 2014
  • Purpose: This study was conducted in order to evaluate the reliability, validity, sensitivity, and specificity of the Short Form of Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS-SF). Methods: A validation study was conducted on 207 elderly patients aged over 65 who were admitted to Bobath Memorial Hospital. Fall risk scores of BMFRAS, composed of eight subscales (age, fall history, physical activity, consciousness level, communication, fall risk factors, underlying disease, and medications) were assessed from the electronic medical record. BMFRAS-SF was derived from eight subscales of the BMFRAS representing the significance between fallers and non-fallers (fall history, physical activity, fall risk factors, underlying disease, and medications). Internal consistency reliability and interrater reliability were assessed by Cronbach's alpha and kappa coefficient. Validity was assessed by Spearman correlation analysis, factor analysis. Sensitivity, specificity, positive predictive and negative predictive values, and a receiver-operating characteristic curve (ROC) were generated. Results: Fallers had significantly higher risk scores than non-fallers in fall history, physical activity, fall risk factors, underlying disease, and medication scales. The BMFRAS-SF demonstrated acceptable Cronbach's alpha (.706) and kappa coefficients of .95. The BMFRAS-SF subscales showed good convergent validity and construct validity. The BMFRAS-SF presented good sensitivity(86.7%), specificity(67.9%), positive predictive value(42.9%) and good negative predictive value(94.8%) at a cut-off score of 5. Areas under the ROC curves were .860 for the BMFRAS and .861 for the BMFRAS-SF. Conclusion: The BMFRAS-SF was proved to be reliable and valid. It could be used for time-saving assessment and evaluation of the high risks for falls in clinical practice settings.

Gamma Knife Surgery for Brain Metastasis from Renal Cell Carcinoma : Relationship Between Radiological Characteristics and Initial Tumor Response

  • Kim, Jin-Wook;Han, Jung-Ho;Park, Chul-Kee;Chung, Hyun-Tai;Paek, Sun-Ha;Kim, Dong-Gyu
    • Journal of Korean Neurosurgical Society
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    • v.42 no.2
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    • pp.92-96
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    • 2007
  • Objective : The authors have speculated that metastatic brain lesions from renal cell carcinoma (RCC) show diverse radiological patterns and tumor responses after Gamma knife surgery (GKS), and have hypothesized that these can be predicted from tumor radiological characteristics. The goal of the current study was to identify the radiological characteristics of RCC brain metastases and the predictors of initial radiosurgical response after GKS. Methods : A retrospective analysis was performed on 48 lesions in 18 patients with RCC brain metastasis treated by GKS. The radiological characteristics of these lesions in magnetic resonance images (MRI) were classified into 3 categories according to enhancement patterns in T1-weighted images and signal intensity characteristics in T2-weighted images. Responses to GKS were analyzed according to these categories, and in addition, other potential predictive factors were also evaluated. Results : MRI findings in the three categories were diverse, though numbers of the lesion were comparable. At 2-month MRI follow-ups after GKS, response rate was 54% and the local tumor control rate 83%. T2 signal intensity was found to be the principal predictive factor of response to GKS, namely negative predictive factor. Other variables such as age, sex, tumor volume, dose, duration from initial diagnosis to GKS, and previous systemic therapies failed to show significant relationships with treatment response by multivariate analysis. Conclusion : Careful evaluation of the radiological characteristics of brain metastases from RCC is important prior to GKS because MRI heterogeneity has predictive value in terms of determining initial tumor response.

To Predict Body Composition of Children and Adolescents by BIA in China

  • Zhang Li-Wei;Zhai Feng-Ying;Yu Wen-Tao;Huang Lei;Wang Hui-Jun
    • Journal of Community Nutrition
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    • v.6 no.3
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    • pp.121-124
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    • 2004
  • Objective : The paper aims to provide predictive coefficients via BIA for the assessment of body composition in children and adolescents to serve clinical as well as research purposes. Methods : Body composition via dual-energy x­ray absorptiometry (DXA) and bioelectric impedance as well as other anthropometric index were derived from meaurements on 1026 children and adolescents aged from 6 to 18 years from Beijing City. The best subset regression and principle component analysis were adopted to build the predictive coefficients with the logarithm of body composition via DXA as response variable. Results : Condition index ${\varphi}$ of fat-free mass multiple linear regression achieves 113.49 and 91.18 for males and females respectively, demonstrating severe multicollinearity among anthropometric indexes in children and adolescents. BIA predictive coefficients base on the best subset regression and principle component analysis boast a content predictive value for lean mass ($r^2$ = 0.9697 and 0.9664 for boys and girls respectively, p < 0.0001) and for Fat$\%$ ($r^2$ = 0.7705 and 0.6959 for boys and girls respectively, p < 0.0001). Conclusions : BIA method is applicable for the prediction of body composition for children and adolescents.