• International Journal of Fluid Machinery and Systems
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• v.5 no.4
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• pp.143-151
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• 2012

Predicting the future condition of machine and assessing the remaining useful life are the center of prognostics. This paper contributes a new prognostic method based on grey model and survival probability. The first step of the method is building a normal condition model then determining the error indicator. In the second step, the survival probability value is obtained based on the error indicator. Finally, grey model coupled with one-step-ahead forecasting technique are employed in the last step. This work has developed a modified grey model in order to improve the accuracy of prediction. For evaluating the proposed method, real trending data of low methane compressor acquired from condition monitoring routine were employed.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1858-1874
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• 2021

Recent advances in the molecular and genetic characterization of central nervous system (CNS) tumors have ushered in a new era of tumor classification, diagnosis, and prognostic assessment. In this emerging and rapidly evolving molecular genetic era, imaging plays a critical role in the preoperative diagnosis and surgical planning, molecular marker prediction, targeted treatment planning, and post-therapy assessment of CNS tumors. This review provides an overview of the current imaging methods relevant to the molecular genetic classification of CNS tumors. Specifically, we focused on 1) the correlates between imaging features and specific molecular genetic markers and 2) the post-therapy imaging used for therapeutic assessment.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.701-710
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• 2012

Retinitis Pigmentosa(RP) is a common hereditary disease. While they have been normally living, those who have this symptom feel frustration and pain by the damage of visual acuity. At the national level, the loss of the economic activity due to the reduction of economically active population will be also greater. There is an urgent need for the base study that can provide the clinical prognosis information of RP disease. In this study, we suggest that it is possible to predict prognosis through the pattern classification of RP data. Statistical processing results through statistical software like SPSS(Statistical Package for the Social Service) were mainly applied for the conventional study in data analysis. However, machine learning and automatic pattern classification was applied to this study. SVM(Support Vector Machine) and other various pattern classifiers were used for it. The proposed method confirmed the possibility of prognostic prediction based on the result of automatically classified RP data by SVM classifier.

• Journal of Gastric Cancer
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• v.11 no.2
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• pp.94-100
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• 2011

Purpose: The 7th AJCC tumor node metastasis (TNM) staging system modified the classification of the lymph node metastasis widely compared to the 6th edition. To evaluate the prognostic predictability of the new TNM staging system, we analyzed the survival rate of the gastric cancer patients assessed by the 7th staging system. Materials and Methods: Among 2,083 patients who underwent resection for gastric cancer at the department of surgery, Hanyang Medical Center from July 1992 to December 2009, This study retrospectively reviewed 5-year survival rate (5YSR) of 624 patients (TanyN3M0: 464 patients, TanyNanyM1: 160 patients) focusing on the number of metastatic lymph node and distant metastasis. We evaluated the applicability of the new staging system. Results: There were no significant differences in 5YSR between stage IIIC with more than 29 metastatic lymph nodes and stage IV (P=0.053). No significant differences were observed between stage IIIB with more than 28 metastatic lymph nodes and stage IV (P=0.093). Distinct survival differences were present between patients who were categorized as TanyN3M0 with 7 to 32 metastatic lymph nodes and stage IV. But patients with more than 33 metastatic lymph nodes did not show any significant differences compared to stage IV (P=0.055). Among patients with TanyN3M0, statistical significances were seen between patients with 7 to 30 metastatic lymph nodes and those with more than 31 metastatic lymph nodes. Conclusions: In the new staging system, modifications of N classification is mandatory to improve prognostic prediction. Further study involving a greater number of cases is required to demonstrate the most appropriate cutoffs for N classification.

• Health Policy and Management
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• v.19 no.4
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• pp.18-32
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• 2009

The goal of this study was to predict the health outcomes of lung cancer surgery based on the Charlson comorbidity index (CCI). An attempt was likewise made to assess the prognostic value of such data for predicting mortality, survival rate, and length of hospital stay. A medical-record review of 389 patients with non-small-cell lung cancer was performed. To evaluate the agreement, the kappa coefficient was tested. Logistic-regression analysis was also conducted within two years after the surgery to determine the association of CCI with death. Survival and multiple-regression analyses were used to evaluate the relationship between CCI and the hospital care outcomes within two-year survival after lung cancer surgery and the length of hospital stay. The results of the study showed that CCI is a valid prognostic indicator of two-year mortality and length of hospital stay, and that it shows the health outcomes, such as death, survival rate, and length of hospital stay, after the surgery, thus enabling the development and application of the methodology using a systematic and objective scale for the results.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3331-3335
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• 2013

Background: The incidence of prostate cancer, one of the most common cancers in elderly men, is increasing annually in Thailand. Matrix metalloproteinase 11 (MMP-11) is a member of the extracellular matrix metalloproteases which has been associated with human tumor progression and clinical outcome. Aim: To quantify MMP-11 expression in prostatic adenocarcinoma tissues and to determine whether its overexpression correlates with survival outcome, and to assess its potential as a new prognostic marker. Materials and Methods: Expression of MMP-11 was analyzed using immunohistochemistry in 103 Thai patients with prostatic adenocarcinoma. Overall survival was analyzed using Kaplan-Meier methods and Cox regression models. Results: Immunoreactivity of MMP-11 was seen in the stroma of prostatic adenocarcinoma tissue samples, high expression being significantly correlated with poor differentiation in Gleason grading, pathologic tumor stage 4 (pT4), and positive-bone metastasis (p<0.05), but not age and prostatic-specific antigen (PSA) level. Patients with high levels of MMP-11 expression demonstrated significantly shorter survival (p<0.001) when compared to those with low levels. Multivariate analysis showed that MMP-11 expression and pT stage were related with survival in prostatic adenocarcinoma [hazard ratio (HR)=0.448, 95% confidence interval (95%CI)=0.212-0.946, HR=0.333, 95%CI=0.15-0.74, respectively]. Conclusions: Expression of MMP-11 is significantly associated with survival in prostatic adenocarcinoma. High levels may potentially be used for prediction of a poor prognosis.

• Journal of Hospice and Palliative Care
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• v.5 no.2
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• pp.111-124
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• 2002

Purpose : Although the average life expectancy has increased due to advances in medicine, mortality due to cancer is on an increasing trend. Consequently, the number of terminally ill cancer patients is also on the rise. Predicting the survival period is an important issue in the treatment of terminally ill cancer patients since the choice of treatment would vary significantly by the patents, their families, and physicians according to the expected survival. Therefore, we investigated the prognostic factors for increased mortality risk in terminally ill cancer patients to help treat these patients by predicting the survival period. Methods : We investigated 31 clinical parameters in 157 terminally ill cancer patients admitted to in the Department of Family Medicine, National Health Insurance Corporation Ilsan Hospital between July 1, 2000 and August 31, 2001. We confirmed the patients' survival as of October 31, 2001 based on medical records and personal data. The survival rates and median survival times were estimated by the Kaplan-Meier method and Log-rank test was used to compare the differences between the survival rates according to each clinical parameter. Cox's proportional hazard model was used to determine the most predictive subset from the prognostic factors among many clinical parameters which affect the risk of death. We predicted the mean, median, the first quartile value and third quartile value of the expected lifetimes by Weibull proportional hazard regression model. Results : Out of 157 patients, 79 were male (50.3%). The mean age was $65.1{\pm}13.0$ years in males and was $64.3{\pm}13.7$ years in females. The most prevalent cancer was gastric cancer (36 patients, 22.9%), followed by lung cancer (27, 17.2%), and cervical cancer (20, 12.7%). The survival time decreased with to the following factors; mental change, anorexia, hypotension, poor performance status, leukocytosis, neutrophilia, elevated serum creatinine level, hypoalbuminemia, hyperbilirubinemia, elevated SGPT, prolonged prothrombin time (PT), prolonged activated partial thromboplastin time (aPTT), hyponatremia, and hyperkalemia. Among these factors, poor performance status, neutrophilia, prolonged PT and aPTT were significant prognostic factors of death risk in these patients according to the results of Cox's proportional hazard model. We predicted that the median life expectancy was 3.0 days when all of the above 4 factors were present, $5.7{\sim}8.2$ days when 3 of these 4 factors were present, $11.4{\sim}20.0$ days when 2 of the 4 were present, and $27.9{\sim}40.0$ when 1 of the 4 was present, and 77 days when none of these 4 factors were present. Conclusions : In terminally ill cancer patients, we found that the prognostic factors related to reduced survival time were poor performance status, neutrophilia, prolonged PT and prolonged am. The four prognostic factors enabled the prediction of life expectancy in terminally ill cancer patients.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2091-2095
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• 2013

Background: The $7^{th}$ TNM staging is the first authoritative standard for evaluation of effectiveness of treatment of gastric cancer worldwide. However, revision of pN classification within TNM needs to be discussed. In particular, the N3 sub-stage is becoming more conspicuous. Methods: Clinical data of 302 pN3M0 stage gastric cancer patients who received radical gastrectomy in Tianjin Medical University Cancer Institute and Hospital from January 2001 to May 2006 were retrospectively analyzed. Results: Location of tumor, depth of invasion, extranodal metastasis, gastric resection, combined organs resection, lymph node metastasis, rate of lymph node metastasis, negative lymph nodes count were important prognostic factors of pN3M0 stage gastric cancers. TNM stage was also associated with prognosis. Patients at T2N3M0 stage had a better prognosis than other sub-classification. T3N3M0 and T4aN3aM0 patients had equal prognosis which followed the T2N3M0. T4aN3bM0 and T4bN3aM0 had lower survival rate than the formers. T4bN3bM0 had worst prognosis. In multivariate analysis, TNM stage group and rate of lymph node metastasis were independent prognostic factors. Conclusions: The sub-stage of N3 may be useful for more accurate prediction of prognosis; it should therefore be applied in the TNM stage system.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.929-934
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• 2013

Aim: To analyze the significance of different clinical factors for prognostic prediction in diffuse large B-cell lymphoma (DLBCL) patients. Methods: Two hundred and twenty-seven DLBCL patients were retrospectively reviewed. Patients were managed with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) regimen or rituximab plus the CHOP (RCHOP) regimen. Results: Lactate dehydrogenase (LDH), ${\beta}2$-microglobulin (${\beta}2$-M), B symptoms, Ann Arbor stage and genetic subtypes were statistically relevant in predicting the prognosis of the overall survival (OS). In the CHOP group, the OS in patients with germinal center B-cell-like (GCB)(76.2%) was significantly higher than that of the non-GCB group (51.9%, P=0.032). With RCHOP management, there was no statistical difference in OS between the GCB (88.4%) and non-GCB groups (81.9%, P=0.288). Conclusion: Elevated LDH and ${\beta}2$-M levels, positive B symptoms, Ann Arbor stage III/IV, and primary nodal lymphoma indicate an unfavorable prognosis of DLBCL patients. Patients with GCB-like DLBCL have a better prognosis than those with non-GCB when treated with the CHOP regimen. The RCHOP treatment with the addition of rituximab can improve the prognosis of patients with DLBCL.

• Journal of Cardiovascular Imaging
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• v.30 no.3
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• pp.185-196
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• 2022

BACKGROUND: Two-dimensional (2D) strain provides more predictive power than ejection fraction (EF) in patients with ST-elevation myocardial infarction (STEMI). 3D strain and EF are also expected to have better clinical usefulness and overcome several inherent limitations of 2D strain. We aimed to clarify the prognostic significance of 3D strain analysis in patients with STEMI. METHODS: Patients who underwent successful revascularization for STEMI were retrospectively recruited. In addition to conventional parameters, 3D EF, global longitudinal strain (GLS), global area strain (GAS), as well as 2D GLS were obtained. We constructed a composite outcome consisting of all-cause death or re-hospitalization for acute heart failure or ventricular arrhythmia. RESULTS: Of 632 STEMI patients, 545 patients (86.2%) had a reliable 3D strain analysis. During median follow-up of 49.5 months, 55 (10.1%) patients experienced the adverse outcome. Left ventricle EF, 2D GLS, 3D EF, 3D GLS, and 3D GAS were significantly associated with poor outcomes. (all, p < 0.001) The maximum likelihood-ratio test was performed to evaluate the additional prognostic value of 2D GLS or 3D GLS over the prognostic model consisting of clinical characteristics and EF, and the likelihood ratio was 15.9 for 2D GLS (p < 0.001) and 1.49 for 3D GLS (p = 0.22). CONCLUSIONS: The predictive power of 3D strain was slightly lower than the 2D strain. Although we can obtain 3D strains, volume, and EF simultaneously in same cycle, the clinical implications of 3D strains in STEMI need to be investigated further.