• Journal of Yeungnam Medical Science
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• v.38 no.4
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• pp.318-325
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• 2021

Background: The diagnosis and prediction of prognosis are important in patients with sepsis, and presepsin is helpful. In this study, we aimed to examine the usefulness of presepsin in predicting the prognosis of sepsis in Korea. Methods: Patients diagnosed with sepsis according to the sepsis-3 criteria were recruited into the study and classified into surviving and non-surviving groups based on in-hospital mortality. A total of 153 patients (32 and 121 patients with sepsis and septic shock, respectively) were included from July 2019 to August 2020. Results: Among the 153 patients with sepsis, 91 and 62 were in the survivor and non-survivor groups, respectively. Presepsin (p=0.004) and lactate (p=0.003) levels and the sequential organ failure assessment (SOFA) score (p<0.001) were higher in the non-survivor group. Receiver operating characteristic curve analysis revealed poor performances of presepsin and lactate in predicting the prognosis of sepsis (presepsin: area under the curve [AUC]=0.656, p=0.001; lactate: AUC=0.646, p=0.003). The SOFA score showed the best performance, with the highest AUC value (AUC=0.751, p<0.001). The prognostic cutoff point for presepsin was 1,176 pg/mL. Presepsin levels higher than 1,176 pg/mL (odds ratio [OR], 3.352; p<0.001), higher lactate levels (OR, 1.203; p=0.003), and higher SOFA score (OR, 1.249; p<0.001) were risk factors for in-hospital mortality. Conclusion: Presepsin levels were higher in non-survivors than in survivors. Thus, presepsin may be a valuable biomarker in predicting the prognosis of sepsis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.83-91
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• 2021

Health is an outset of psychological, social, financial, and physical state. Several macroeconomic factors are entangled with health and mortality. Infant mortality and life expectancy are two keyguard on demographic research context on last few decades. On the other hand, foreign inflows play an unprecedent role for raising economic circulation and providing more opportunities to build a better society. The study aims to investigate the relationship between foreign direct investment (FDI), economic growth, and Bangladesh's health. This study employs time-series data from 1980 to 2018. Results show, with Auto-regressive Distribute Lag (ARDL) model, that there is significant cointegration among variables. Foreign investment and economic output relate significantly and positively to health. On the contrary, education is quasi-linked with a different sign-on different model. For model validation, pitfalls of time-series multicollinearity, heteroscedasiticy, and autocorrelation are not present. Also, CUSUM and CUSUMSQ tests are validating the model as stable and fit for future prediction. Medical assessment and education need more attention from the government as well as the private sector. FDI can play a catalyst role for improving the health sector, raising opportunity in educating and creating a better lifestyle. In order to optimize foreign investment, the government should implement necessary reforms and policies.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.322-330
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• 2021

In modern aquaculture, mass mortality is a very important issue that determines the success of aquaculture business. If a fish disease is not detected at an early stage in the farm, the disease spreads quickly because the farm is a closed environment. Therefore, early detection of diseases is crucial to prevent mass mortality of fish raised in farms. Recently deep learning-based automatic identification of fish diseases has been widely used, but there are many difficulties in identifying objects due to insufficient images of fish diseases. Therefore, this paper suggests a method to generate a large number of fish disease images by synthesizing normal images and disease images using SinGAN deep learning model in order to to solve the lack of fish disease images. We generate images from the three most frequently occurring Paralichthys Olivaceus diseases such as Scuticociliatida, Vibriosis, and Lymphocytosis and compare them with the original image. In this study, a total of 330 sheets of scutica disease, 110 sheets of vibrioemia, and 110 sheets of limphosis were made by synthesizing 10 disease patterns with 11 normal halibut images, and 1,320 images were produced by quadrupling the images.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.5
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• pp.423-429
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• 2001

Prediction of the variation in annual biomass was conducted for the white croaker. Argyrosomus argentatus in Korean waters using leslie Matrix, based upon fishery data for the past 21 years and biological data, We used density-independent and density-dependent Leslie Matrix models. Similar parameters were estimated from two models except that the density-dependent model was influenced by the density effect variable, q(i,t), The eigenvalue of the white croaker population for the $1984\~1995$ period was estimated to be 0.8, indicating a declining pattern of the population. The survival rate of 0-th year class was calculated to be 0.00005. Based on the schedule of the age-specific survival rate and fecundity, the future biomass and catch was predicted for various levels of fishing mortalities (F), If F was set at 0.252/yr ($F_{35x}$) or 0.368/yr ($F_{0.1}$), the biomass and catch increased, and if F was set at 0.922 ($F_{current}$), the biomass and catch decreased, The fishing mortality at equilibrium was estimated to be 0.7/yr. Finally, the management strategy of the white croaker was discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1863-1870
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• 2013

The purpose of this study is when the cases will be found, used as a basic data for clinical severity prediction, and research on suicide prevention. By classifying the group of survival and death about the patients who visit the Emergency Medical Center by attempt suicide by drug addiction, identifying the condition when visiting and results of the treatment after visiting. From June 2009 to May 2011, last two years data that among the drug abusers who visited the Emergency Medical Center in C-University Hospital in Gwang-Ju, only suicidal patients, except with unintentional accidents were collected. The findings, among the drug addiction patients who high age, lower level of education and living alone were the mortality rate was higher. And if who drunk the agricultural chemicals, the convalescence was not good. If the causes of suicide were economic problems and depression, the mortality rate was higher. And when visit hospital, if the consciousness was stupor and semi-coma/coma, the convalescence was not good. As grasp the risk for suicide patients of drug addiction, help on the Prediction of clinical severity, also stamp the appropriate drug education with psychological support is more important on them.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.260-268
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• 2024

Cervical cancer is the fourth most common cancer in women worldwide, and more than 604,000 new cases were reported in 2020 alone, resulting in approximately 341,831 deaths. The Cox regression model is a major model widely adopted in cancer research, but considering the existence of nonlinear associations, it faces limitations due to linear assumptions. To address this problem, this paper proposes ResSurvNet, a new model that improves the accuracy of cervical cancer mortality prediction using ResNet's residual learning framework. This model showed accuracy that outperforms the DNN, CPH, CoxLasso, Cox Gradient Boost, and RSF models compared in this study. As this model showed accuracy that outperformed the DNN, CPH, CoxLasso, Cox Gradient Boost, and RSF models compared in this study, this excellent predictive performance demonstrates great value in early diagnosis and treatment strategy establishment in the management of cervical cancer patients and represents significant progress in the field of survival analysis.

• Journal of Korean Neurosurgical Society
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• v.67 no.1
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• pp.94-102
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• 2024

Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.

• Biomolecules & Therapeutics
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• v.28 no.6
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• pp.491-502
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• 2020

Sex/gender disparity has been shown in the incidence and prognosis of many types of diseases, probably due to differences in genes, physiological conditions such as hormones, and lifestyle between the sexes. The mortality and survival rates of many cancers, especially liver cancer, differ between men and women. Due to the pronounced sex/gender disparity, considering sex/gender may be necessary for the diagnosis and treatment of liver cancer. By analyzing research articles through a PubMed literature search, the present review identified 12 genes which showed practical relevance to cancer and sex disparities. Among the 12 sex-specific genes, 7 genes (BAP1, CTNNB1, FOXA1, GSTO1, GSTP1, IL6, and SRPK1) showed sex-biased function in liver cancer. Here we summarized previous findings of cancer molecular signature including our own analysis, and showed that sex-biased molecular signature CTNNB1^High, IL6^High, RHOA^High and GLIPR1^Low may serve as a female-specific index for prediction and evaluation of OS in liver cancer patients. This review suggests a potential implication of sex-biased molecular signature in liver cancer, providing a useful information on diagnosis and prediction of disease progression based on gender.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6645-6650
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• 2015

Background: Gastric cancer (GC) is the third most common cancer regarding mortality in the world. The cag pathogenicity island (PAI) of Helicobacter pylori which contains genes associated with a more aggressive phenotype may involve in the pathogenesis of gastrointestinal disease. We here aimed to examine the associations of cagH, cagL, orf17, and cagG genotypes of H. pylori cag PAI with severe gastrointestinal disease. Materials and Methods: A total of 242 H. pylori strains were genotyped. Histopathological examination and classification of subjects were performed. Results: The frequencies of the cagH, cagL, cagG, and orf17 genotypes were 40/54 (74.1%), 53/54 (98.1%), 38/54 (70.4%), and 43/54 (79.6%), respectively, in patients with peptidic ulceration (PU),while in the control group, the frequencies were 87/147 (59.6%) for cagH, 121/146 (82.9%) for cagL, 109/146 (74.7%) for cagG, and 89/146 (61.0%) for orf17. The results of simple logistic regression analysis showed that the cagL and orf17 genotypes were significantly associated with an increased risk of PU not GC; the ORs (95% CI) were 10.950 (1.446-82.935), and 2.504 (1.193-5.253), respectively. No significant association was found between the cagH and cagG genotypes and the risk of both the PU and the GC in Iran (P>0.05). Finally, multiple logistic regression analysis showed that the cagL genotype was independently and significantly associated with the age-and sex-adjusted risk for PU; the OR (95% CI) was 9.557 (1.219-17.185). Conclusions: We conclude that the orf17 and especially cagL genotypes of H. pylori cag PAI could be factors for risk prediction of PU, but not GC in Iran.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.175-182
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• 2011

This study proposes CAOPI(Computer Aided Organ Prediction Index) system based on APACHE II(Acute Physiology And Chronic Health Evaluation) for classifying disease severity and predicting the conditions of patients' major organs. The existing ICU disease severity evaluation is mostly about calculating risk scores using patients' data at certain points, which has limitations on making precise treatments. CAOPI system is designed to provide personalized treatments by classifying accurate severity degrees of emergency patients, predicting patients' mortality rate and scoring the conditions of certain organs.