• Journal of Genetic Medicine
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• v.7 no.2
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• pp.138-144
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• 2010

Purpose: Endothelial progenitor cells (EPCs), which mediates neovascularization of uterine endometrium may be involved in the neovascularization in the utero-placental circulation. Low numbers of endothelial progenitor colony-forming unit (CFU) in culture are predictive biomarker of vascular disease. The aim of the present study was to evaluate whether the number of CFU in preeclampsia differed from that in normal pregnancy. Materials and Methods: Women with singleton normal (n=26) or preeclamptic (n=20) pregnancies were studied during the third trimester. The number of EPCs was quantified by CFU methodology. Plasma levels of angiogenic factors, vascular endothelial growth factor (VEGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and placental growth factor (PlGF) were determined by enzyme-linked immunoassay. Results: CFU numbers were significantly decreased in the preeclamptic patients compared with the controls (median, 3; range 1-12 vs. 31; 3-81 CFU/well, P<0.001). A majority of the cells comprising individual colonies were positive for endothelial characteristics (Ulex europaeus lectin staining and acetylated low-density lipoprotein uptake). Plasma levels of the sFlt-1 were highly elevated (P<0.001) in patient with preeclampsia compared to controls, whereas PlGF were highly reduced (P=0.004), but these factors did not associate with CFU numbers. Conclusion: Our results suggest that reduced numbers of CFU obtained from maternal peripheral blood may contribute to the development of preeclampsia.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.76-82
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• 2011

Purpose: Lymphoscintigraphy is absolutely being used standard examination in lymphatic diagnosis, evaluation after treatment, and it is useful for lymphedema to plan therapy. In case of lymphoscintigraphy of lower-extremity lymphedema, it had an effect on results if patients had not pose same position on the examination of 1 min, 1 hour and 2 hours after injection. So we'll study the methods to improve confidence with minimized quantitative analysis errors by influence factors. Materials and Methods: Being used the Infinia of GE Co. we injected $^{99m}Tc$-phytate 37 MBq (1.0 mCi) 4 sylinges into 40 people's feet hypodermically from June to August 2010 in Samsung Medical Center. After we acquired images of fixed and unfixed condition, we confirmed the count values change by attenuation of soft tissue and bone according to different feet position. And we estimated 5 times increasing 2 cm of distance between $^{99m}Tc$ point source and detector each time to check counts difference according to distance change by different feet position. Finally, we compared 1 and 6 min lymphoscintigraphy images with same position to check the effect of quantitative analysis results owing to difference of amounts of movement of the $^{99m}Tc$-phytate in the lymphatic duct. Results: Percentage difference regarding error values showed minimum 2.7% and maximum 25.8% when comparing fixed and unfixed feet position of lymphoscintigraphy examination at 1 min after injection. And count values according to distance were 173,661 (2 cm), 172,095 (4 cm), 170,996 (6 cm), 167,677 (8 cm), 169,208 counts (10 cm) which distance was increased interval of 2 cm and basal value was mean 176,587 counts, and percentage difference values were not over 2.5% such as 1.27, 1.79, 2.04, 2.42, 2.35%. Also, Assessment results about amounts of movement in lymphatic duct within 6 min until scanning after injection showed minimum 0.15%, and maximum 2.3% which were amounts of movement. We can recognize that error values represent over 20% due to only attenuation of soft tissue and bone except for distance difference (2.42%) and amounts of movement in lymphatic duct (2.3%). Conclusion: It was show that if same patients posed different feet position on the examination of 1 min, 1 hour and 2 hours after injection in the lymphoscintigraphy which is evaluating lymphatic flow of patients with lymphedema and analyzing amount of intake by lymphatic system, maximum error value represented 25.8% due to attenuation of soft tissue and bone, and PASW (Predictive Analytics Software) showed that fixed and unfixed feet position was different each other. And difference of distance between detector and feet and change of count values by difference of examination beginning time after injection influence on quantitative analysis results partially. Therefore, we'll make an effort to fix feet position and make the most of fixing board in lymphoscintigraphy with quantitative analysis.

• 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.

• Tuberculosis and Respiratory Diseases
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• v.51 no.6
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• pp.559-569
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• 2001

Background : Pleural effusion is one of the most common clinical manifestations associated with a variety of pulmonary diseases such as malignancy, tuberculosis, and pneumonia. However, there are no useful laboratory tests to determine the specific cause of pleural effusion. Therefore, an attempt was made to analyze the various types of pleural effusion and search for useful laboratory tests for pleural effusion in order to differentiate between the diseases, especially between a malignant pleural effusion and a non-malignant pleural effusion. Methods : 93 patients with a pleural effusion, who visited the Severance hospital from January 1998 to August 1999, were enrolled in this study. Ultrasound-guided thoracentesis was done and a confirmational diagnosis was made by a gram stain, bacterial culture, Ziehl-Neelsen stain, a mycobacterial culture, a pleural biopsy and cytology. Results : The male to female ratio was 56 : 37 and the average age was $47.1{\pm}21.8$ years. There were 16 cases with a malignant effusion, 12 cases with a para-malignant effusion, 36 cases with tuberculosis, 22 cases with a para-pneumonic effusion, and 7 cases with transudate. The LDH2 fraction was significantly higher in the para-malignant effusion group compared to the para-pneumonic effusion group [$30.6{\pm}6.4%$ and $20.2{\pm}7.5%$, respectively (p<0.05)] and both the LDH1 and LDH2 fraction was significantly in the para-malignant effusion group compared to those with tuberculosis [$16.4{\pm}7.2%$ vs. $7.6{\pm}4.7%$, and $30.6{\pm}6.4%$ vs.$17.6{\pm}6.3%$, respectively (p<0.05)]. The pleural effusion/serum LDH4 fraction ratio was significantly lower in the malignant effusion group compared to those with tuberculosis [$1.5{\pm}0.8$ vs. $2.1{\pm}0.6$, respectively (p<0.05)]. The LDH4 fraction and the pleural effusion/serum LDH4 fraction ratio was significantly lower in the para-malignant effusion group compared to those with tuberculosis [$17.0{\pm}5.8%$ vs. $23.5{\pm}4.6%$ and $1.3{\pm}0.4$ vs. $2.1{\pm}0.6$, respectively (p<0.05)]. Conclusion : These results suggest that the LDH isoenzyme was the only useful biochemical test for a differential diagnosis of the various diseases. In particular, the most useful test was the pleural effusion/serum LDH4 fraction ratio to distinguish between a para-malignant effusion and a tuberculous effusion.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Clinical and Experimental Pediatrics
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• v.46 no.2
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• pp.173-177
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• 2003

Purpose : Recently, different results about factors affecting accurate quantitation of 24-hr urinary protein(24UP) amount using spot urine protein/creatinine ratio(PCR) have been reported. The current study was designed to evaluate correlation between 24UP amounts and PCR in children, and the effect of 24UP amounts, age, sex, and glomerular filtration rate(GFR) on this correlation. Methods : Among 94 patients who visited the department of pediatrics in Busan Paik Hospital from March 2002 to August 2002, 68 patients whose urinary creatinine excretion was ${\geq}15mg/kg/day$ were included in this study. All the patients were divided into I, II/A, B group(I : 24UP<500 mg/day, II : $24UP{\geq}500mg/day$, A : <10 years of age, B : ${\geq}10years$ of age). Pearson correlation analysis was performed between 24UP and PCR to evaluate the relationship. We defined fractional difference between 24UP and PCR, and then performed multiple regression analysis with 24UP amount, age, GFR and fractional difference. Results : There was a strong positive linear correlation between 24UP and PCR(R=0.936, P<0.0001) in all patients, and the correlation was also good in each group. Using PCR cutoff values of 0.5, the PCR provided high sensitivity, specificity, positive and negative predictive value in predicting 24UP amount ${\geq}500mg$. The factors affecting accurate quantitation of proteinuria using spot urine PCR was age, not 24UP amount, GFR or sex. Conclusion : Spot urine PCR is a useful test but has limitations in predicting 24UP amount. Therefore, it should be used only as screening method. Age-adjusted PCR cutoff values may be necessary to predict 24UP amount in children with proteinuria.

• Tuberculosis and Respiratory Diseases
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• v.62 no.5
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• pp.374-381
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• 2007

Background: This study evaluated which CT findings could be used to predict the negative results of a sputum smear in patients with active pulmonary tuberculosis and multiple cavities. Methods: Thirty-eight patients with active pulmonary tuberculosis and multiple cavities on CT were classified into 2 groups: smear-positive (n = 30) and -negative (n = 8). The CT findings were reviewed retrospectively. The maximum internal diameter of the largest cavity, the number of the cavities and lobes with cavities, and the characteristics of the associated findings such as consolidation, ground glass opacity, micronodules and nodule were accessed. The number of cavities above 20 mm in the maximum internal diameter and a necrotizing pneumonia-like pattern were also evaluated. Result: The maximum internal diameter and number of cavities was $32.23{\pm}17.66mm$ and $15.50{\pm}11.12mm$ (p = 0.0042), and $5.53{\pm}3.17$ and $2.43{\pm}1.13$ (p = 0.0002) in the smear-positive and -negative group, respectively. Three or more cavities were observed at 76.7% and 12.5% in the smear-positive and -negative group, respectively (p < 0.005). There were $2.00{\pm}1.34$ and $0.25{\pm}0.46$ (p = 0.001), and $1.5{\pm}1.50$ and $0.38{\pm}0.52$ (p =0.0016) lobes with consolidation and ground glass opacity in the smear-positive and -negative group, respectively. A necrotizing pneumonia-like pattern was observed in 43.3% of the smear-positive group only. The other findings were similar in both two groups. The sensitivity, specificity, positive and negative predictive value for the presence of at least a finding of consolidation, more than 3 cavities or the largest cavity > 20 mm in the maximum internal diameter were 100%, 62.5%, 90.9%, and 100%, respectively. Conclusion: Two cavities 20 mm or less in the maximum internal diameter without consolidation on CT might be associated with a negative result of the sputum smear in patients with active pulmonary tuberculosis and multiple cavities.

• Tuberculosis and Respiratory Diseases
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• v.43 no.4
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• pp.590-599
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• 1996

Background : Bronchial artery embolization has been established as an effective means to control hemoptysis, especially in patients with decreased pulmonary function and those with advanced chronic obstructive pulmonary disease. We evaluated the effect of arterial embolization in immediate control of massive hemoptysis and investigated the clinical and angiographic characteristics and the course of patients with reccurrent hemoptysis after initial succeseful embolization. Another purpose of this study was to find predictive that cause rebleeding after bronchial artery embolization. Method : We reviewed 47 cases that underwent bronchial artery embolization for the management of massive hemoptysis, retrospectively. We analyzed angiographic findings in all cases before bronchial artery embolization and also reviewed the angiographic findings of patients that underwent additional bronchial artery embolization for the control of reccurrent hemoptysis to find the clauses of rebleeding. Results : 1) Underlying causes of hemoptysis were pulmonary tuberculosis(n=35), bronchiectasis(n=5), aspergilloma(n=2), lung cancer(n=2), pulmonary A-V malformation(n=1), and unknown cases(n=2). 2) Overal immediate success rate was 94%(n=44), an6 recurrence rate was 40%(n=19). 3) The prognostic factors such as bilaterality, systemic-pulmonary artery shunt, multiple feeding arteries and degree of neovascularity were not statistically correlated with rebleeding tendency (p value>0.05). 4) At additional bronchial artery embolization, Revealed recannalization of previous embolized arteries were 14/18cases(78%) and the presence of new deeding arteries was 8/18cases(44%). 5) The complications(31cases, 66%) such as fever, chest pain, cough, voiding difficulty, paralytic ileus, motor and sensory change of lower extremity, atelectasis and splenic infarction were occured. Conclusion : Recannalization of previous embolized arteries is the major cause of recurrence after bronchial artery embolization. Despite high recurrence rate of hemoptysis, bronchial artery embolization for management of massive hemoptysis is a effective and saute procedure in immediate bleeding control.

• The Korean Journal of Nuclear Medicine
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• v.34 no.1
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• pp.39-54
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• 2000

Purpose: Dipyridamole stress myocardial perfusion SPECT could predict prognosis, however, long-term follow-up showed change of hazard ratio in patients with suspected coronary artery disease. We investigated how long normal SPECT could predict the benign prognosis on the long-term follow-up. Materials and Methods: We followed up 1169 patients and divided these patients into groups in whom coronary angiography were performed and were not. Total cardiac event rate and hard event rate were predicted using clinical, angiographic and SPECT findings. Predictive values of normal and abnormal SPECT were examined using survival analysis with Mantel-Haenszel method, multivariate Cox proportional hazard model analysis and newly developed statistical method to test time-invariance of hazard rate and changing point of this rate. Results: Reversible perfusion decrease on myocardial perfusion SPECT predicted higher total cardiac event rate independently and further to angiographic findings. However, myocardial SPECT showed independent but not incremental prognostic values for hard event rate. Hazard ratio of normal perfusion SPECT was changed significantly (p<0.001) and the changing point of hazard rate was 4.4 years of follows up. However, the ratio of abnormal SPECT was not. Conclusion: Dipyridamole stress myocardial perfusion SPECT provided independent prognostic information in patients with known and suspected coronary artery disease. Normal perfusion SPECT predicted least event rate for 4.4 years.