• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.605-612
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• 2011

In multi-center randomized clinical trial the treatment eect may be changed over centers. It is thus important to investigate the heterogeneity in treatment eect between centers. For this, uncorrelated random-eect models assuming independence between random-eect terms have been often used, which may be a strong assumption. In this paper we propose a correlated frailty modelling approach of investigating such heterogeneity using the hierarchical-likelihood method when the outcome is time-to-event. In particular, we show how to construct a proper prediction interval for frailty, which explores graphically the potential heterogeneity for a treatment-by-center interaction term. The proposed method is illustrated via numerical studies based on data from the design of a multi-center clinical trial.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.210-212
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• 1999

This paper proposes a novel wavelet transform based technique for prediction of System Marginal Price(SMP). In this paper, Daubechies D1(haar), D2, D4 wavelet transforms are adopted to predict SMP and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP on the next scheduling day through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for the SMP forecasting.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.463-467
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• 2015

Mega-shock means a sporadic event such as the earning shock, which occurred by sudden market changes, and it can cause serious problems of profit loss of international construction projects. Therefore, the early response and prevention by analyzing and predicting the Mega-shock is critical for successful project delivery. This research is preliminary study to develop a prediction model that supports market condition analysis and Mega-shock forecasting. To avoid disadvantages of classic statistical approaches that assume the market factors are linear and independent and thus have limitations to explain complex interrelationship among a range of international market factors, the research team explored the Fractal Theory that can explain self-similarity and recursiveness of construction market changes. The research first found out correlation of the major market factors by statistically analyzing time-series data. The research then conducted a base of the Fractal analysis to distinguish features of fractal from data. The outcome will have potential to contribute to building up a foundation of the early shock warning system for the strategic international project management.

• Korea Journal of Hospital Management
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• v.11 no.3
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• pp.19-41
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• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.534-539
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• 2010

In genomic studies, thousands of features are collected on relatively few samples. One of the goals of these studies is to build classifiers to predict the outcome of future observations. There are three inherent steps to build classifiers: a significant gene selection, model selection and prediction assessment. In the paper, with a focus on prediction assessment, we normalize microarray data with quantile-normalization methods that adjust quartile of all slide equally and then design a system comparing several methods to estimate 'true' prediction error of a prediction model in the presence of feature selection and compare and analyze a prediction error of them. LOOCV generally performs very well with small MSE and bias, the split sample method and 2-fold CV perform with small sample size very pooly. For computationally burdensome analyses, 10-fold CV may be preferable to LOOCV.

• Journal of Korean Neurosurgical Society
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• v.63 no.2
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• pp.248-260
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• 2020

Objective : To investigate the efficiency of diffusion tensor imaging (DTI) fiber-tracking based neuronavigation and assess its usefulness in the preoperative surgical planning, prognostic prediction, intraoperative course and outcome improvement. Methods : Seventeen patients with cerebral masses adjacent to corticospinal tract (CST) were given standard magnetic resonance imaging and DTI examination. By incorporation of DTI data, the relation between tumor and adjacent white matter tracts was reconstructed and assessed in the neuronavigation system. Distance from tumor border to CST was measured. Results : The sub-portion of CST in closest proximity to tumor was found displaced in all patients. The chief disruptive changes were classified as follows : complete interruption, partial interruption, or simple displacement. Partial interruption was evident in seven patients (41.2%) whose lesions were close to cortex. In the other 10 patients (58.8%), delineated CSTs were intact but distorted. No complete CST interruption was identified. Overall, the mean distance from resection border to CST was 6.12 mm (range, 0-21), as opposed to 8.18 mm (range, 2-21) with simple displacement and 2.33 mm (range, 0-5) with partial interruption. The clinical outcomes were analyzed in groups stratified by intervening distances (close, <5 mm; moderated, 5-10 mm; far, >10 mm). For the primary brain tumor patients, the proportion of completely resected tumors increased progressively from close to far grouping (42.9%, 50%, and 100%, respectively). Five patients out of seven (71.4%) experienced new neurologic deficits postoperatively in the close group. At meantime, motor deterioration was found in six cases in the close group. All patients in the far and moderate groups received excellent (modified Rankin Scale [mRS] score, 0-1) or good (mRS score, 2-3) rankings, but only 57.1% of patients in the close group earned good outcome scores. Conclusion : DTI fiber tracking based neuronavigation has merit in assessing the relation between lesions and adjacent white matter tracts, allowing prediction of patient outcomes based on lesion-CST distance. It has also proven beneficial in formulating surgical strategies.

• Korea Journal of Hospital Management
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• v.14 no.1
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• pp.23-35
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• 2009

The objectives of the present study is to examine the validity of Charlson Comorbidity Index(CCI) based on medical record data; to utilize the index to determine outcome indexes such as mortality, length of stay and cost for the domestic patients whose have received total hip arthroplasty. Based on medical record date, 1-year Mortality was analyzed to be 0.664 of C statistic. The $R^2$ for the predictability for length of stay and the cost was about 0.0181, 0.1842. Fee of national health insurance and total cost including the cost not covered by insurance, also had statistically significance above 3 points of Charlson point score(p=0.0290, 0.0472; $p.{\le}0.05$). The 1-year mortality index, length of stay and cost of the total hip arthroplasty patients which was obtained utilizing CCI have a limitative prediction power and therefore should be carefully analyzed for use.

• Imaging Science in Dentistry
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• v.44 no.3
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• pp.213-220
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• 2014

Purpose: This study was performed to determine the efficacy of observers' prediction for the need of bone grafting and presence of perioperative complications on the basis of cone-beam computed tomography (CBCT) and panoramic radiographic (PAN) planning as compared to the surgical outcome. Materials and Methods: One hundred and eight partially edentulous patients with a need for implant rehabilitation were referred for preoperative imaging. Imaging consisted of PAN and CBCT images. Four observers carried out implant planning using PAN image datasets, and at least one month later, using CBCT image datasets. Based on their own planning, the observers assessed the need for bone graft augmentation as well as complication prediction. The implant length and diameter, the need for bone graft augmentation, and the occurrence of anatomical complications during planning and implant placement were statistically compared. Results: In the 108 patients, 365 implants were installed. Receiver operating characteristic analyses of both PAN and CBCT preoperative planning showed that CBCT performed better than PAN-based planning with respect to the need for bone graft augmentation and perioperative complications. The sensitivity and the specificity of CBCT for implant complications were 96.5% and 90.5%, respectively, and for bone graft augmentation, they were 95.2% and 96.3%, respectively. Significant differences were found between PAN-based planning and the surgery of posterior implant lengths. Conclusion: Our findings indicated that CBCT-based preoperative implant planning enabled treatment planning with a higher degree of prediction and agreement as compared to the surgical standard. In PAN-based surgery, the prediction of implant length was poor.

• Journal of Korean Neurosurgical Society
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• v.30 no.1
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• pp.60-65
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• 2001

Objective : The popular grading systems in use, such as Hunt-Hess grade and Fisher scale score, are based primarily on the patient's clinical conditions or computerized tomography score after aneurysmal subarachnoid hemorrhage(SAH). The author investigated whether the need for ventriculoperitoneal(VP) shunt for chronic hydrocephalus and outcome can be predicted by Hunt-Hess grade and Fisher scale. Methods : A series of 146 patients admitted to our hospital from August 1991 to July 1999, who presented with SAH and underwent craniotomy for aneurysm clipping were studied retrospectively. Chronic hydrocephalus was defined as clinically and radiographically demonstrated hydrocephalus that lasted 2 weeks or longer after initial hemorrhage which required shunting. Patients were evaluated based on following factors : Hunt-Hess grade, Fisher scale, age, sex, hypertension, aneurysm location, and intervals from aneurysm rupture to operation. Results : The overall mortality rate of the study group was 8.2%. Hunt-Hess grade(p=0.001) or Fisher scale (p=0.001) at all pretreatment times was significantly correlated with outcome. In addition, there was an increased risk of poor outcome in older age(65<). However, there were statistically no significant relationship between outcome and sex, location of aneurysm, hypertension, and interval from aneurysmal rupture to operation(p>0.05). Of 134 surviving patients, 16 patients(12%) underwent VP shunt placement secondary to chronic hydrocephalus. Hunt-Hess grade(p=0.001) is more predictive of chronic hydrocephalus than Fisher scale(p=0.146). Aneurysm location was significantly correlated with development of chronic hydrocephalus (p<0.05), without significant correlations in sex, age, hypertension. IVH, and ICH. Conclusion : This study suggests that there is a high clinical correlation between outcome and Hunt-Hess grades and Fisher scales on admission, but Hunt-Hess grade is more predictive for chronic hydrocephalus than Fisher scale. In addition, age(<65 yrs) is the significant factor for prediction of outcome. There was a trend of increasing risk for chronic hydrocephalus according to aneurymal location.

• Korean Journal of Clinical Laboratory Science
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• v.50 no.2
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• pp.126-135
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• 2018

This study examined whether the difference in the middle cerebral artery (MCA) velocities can predict the prognosis of stroke and whether the prognostic impact differs among stroke subtypes. Transient ischemic attack (TIA) or acute ischemic stroke patients, who underwent a routine evaluation and transcranial Doppler (TCD), were included in this study. The MCA asymmetry index was calculated using the relative percentage difference in the mean flow velocity (MFV) between the left and right MCA: (|RMCA MFV-LMCA MFV|/mean MCA MFV)${\times}100$. The stroke subtypes were determined using the TOAST classification. Poor functional outcomes were defined as a mRS score ${\geq}3$ at 3 months after the onset of stroke. A total of 988 patients were included, of whom 157 (15.9%) had a poor functional outcome. Multivariable analysis showed that only the MCA asymmetry index was independently associated with a poor functional outcome. ROC curve analysis showed that adding the MCA asymmetry index to the prediction model improved the discrimination of a poor functional outcome from acute ischemic stroke (from 88.6% [95% CI, 85.2~91.9] to 89.2% [95% CI, 85.9~92.5]). The MCA asymmetry index has an independent prognostic value for predicting a poor short-term functional outcome after an acute cerebral infarction. Therefore, TCD may be useful for predicting a poor functional outcome in patients with acute ischemic stroke.