• International Journal of Safety
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• 제11권1호
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• pp.26-32
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• 2012

This paper introduces a feasibility evaluation method for prognosis systems based on an empirical model in nuclear power plants. By exploiting the dynamical signature characterized by abnormal phenomena, the prognosis technique can be applied to detect the plant abnormal states prior to an unexpected plant trip. Early $operator^{\circ}{\emptyset}s$ awareness can extend available time for operation action; therefore, unexpected plant trip and time-consuming maintenance can be reduced. For the practical application in nuclear power plant, it is important not only to enhance the advantages of prognosis systems, but also to quantify the negative impact in prognosis, e.g., uncertainty. In order to apply these prognosis systems to real nuclear power plants, it is necessary to conduct a feasibility evaluation; the evaluation consists of 4 steps (: the development of an evaluation method, the development of selection criteria for the abnormal state, acquisition and signal processing, and an evaluation experiment). In this paper, we introduce the feasibility evaluation method and propose further study points for applying prognosis systems from KHNP's experiences in testing some prognosis technologies available in the market.

• Asian Pacific Journal of Cancer Prevention
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• 제13권4호
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• pp.1533-1537
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• 2012

In general, breast cancer is the most common malignancy among women in developed as well as some developing countries, often being the second leading cause of cancer mortality after lung cancer. Using a parametric log-logistic model to consider the effects of prognostic factors, the present study focused on the 5-year survival of women with the diagnosis of breast cancer in Southern Iran. A total of 1,148 women who were diagnosed with primary invasive breast cancer from January 2001 to January 2005 were included and divided into three prognosis groups: poor, medium, and good. The survival times as well as the hazard rates of the three different groups were compared. The log-logistic model was employed as the best parametric model which could explain survival times. The hazard rates of the poor and the medium prognosis groups were respectively 13 and 3 times greater than in the good prognosis group. Also, the difference between the overall survival rates of the poor and the medium prognosis groups was highly significant in comparison to the good prognosis group. Use of the parametric log-logistic model - also a proportional odds model - allowed assessment of the natural process of the disease based on hazard and identification of trends.

• 동의생리병리학회지
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• 제26권6호
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• pp.818-822
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• 2012

We in this paper propose a prognosis graph, analyzing prognoses of each pattern described in the Korean medicine literatures. This graph is represented as the integrated graphs about knowledge of patterns and their transitions in the prognoses, where a node becomes a pattern name and a edge becomes a transition between patterns, along with a condition with respect to cause or mechanism of the pattern. The knowledge of prognoses which a pattern is transit into another pattern can be identified at a glance by using this model. We also construct a upper-level prognosis graph, excluding five viscera and six entrails from the model. This upper-level prognosis graph contains the conceptual knowledge than clinical one so that it may be helpful to students and researchers in the Korean medicine fields.

• 전력전자학회논문지
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• 제26권6호
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• pp.381-389
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• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.

• 한국자동차공학회논문집
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• 제18권1호
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• pp.31-36
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• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• Asian Pacific Journal of Cancer Prevention
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• 제13권11호
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• pp.5505-5510
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• 2012

Objective: The aim of this retrospective study is to analyze the clinical and pathological factors related to the prognosis of Chinese patients with stage Ib to IIb cervical cancer. Methods and Results: 13 clinical pathological factors in 255 patients with stage Ib to IIb cervical cancer undergoing radical hysterectomy and systematic lymphadenectomy were analyzed to screen for factors related to prognosis. The cumulative 5-year survival of the 255 patients was 75.7%. The result of the univariate analysis suggested that clinical stage, cell differentiation, depth of cervical stromal invasion, parametrial tissue involvement, and lymph node metastasis were prognostic factors for patients with stage Ib to IIb cervical cancer (P<0.05). Compared with cases with involvement of iliac nodes, obturator nodes, or inguinal lymph nodes, cases with metastasis to the common iliac lymph nodes had a poorer prognosis (P<0.05). Cases with involvement of four or more lymph nodes had a poorer prognosis than those with involvement of three or fewer lymph nodes (P<0.05). Using multivariate Cox proportional hazards model regression analysis, non-squamous histological type, poor differentiation, parametrial tissue involvement, and outer 1/3 stromal invasion were found to be independently related to patients poor prognosis (P<0.05). Conclusion: Non-squamous histological type, poor cell differentiation, parametrial tissue involvement, and outer 1/3 stromal invasion are the independent poor prognostic factors for patients with stage Ib to IIb cervical cancer.

• 대한간호학회지
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• 제49권6호
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• pp.724-735
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• 2019

Purpose: This study was conducted to investigate relationship between delirium, risk factors on delirium, and patient prognosis based on Donabedian's structure-process-outcome model. Methods: This study utilized a path analysis design. We extracted data from the electronic medical records containing delirium screening data. Each five hundred data in a delirium and a non-delirium group were randomly selected from electronic medical records of medical and surgical intensive care patients. Data were analyzed using SPSS 20 and AMOS 24. Results: In the final model, admission via emergency department (Β=.06, p=.019), age over 65 years (Β=.11, p=.001), unconsciousness (Β=.18, p=.001), dependent activities (Β=.12, p=.001), abnormal vital signs (Β=.12, p=.001), pressure ulcer risk (Β=.12, p=.001), enteral nutrition (Β=.12, p=.001), and use of restraint (Β=.30, p=.001) directly affecting delirium accounted for 56.0% of delirium cases. Delirium had a direct effect on hospital mortality (Β=.06, p=.038), hospital length of stay (Β=5.06, p=.010), and discharge to another facility (not home) (Β=.12, p=.001), also risk factors on delirium indirectly affected patient prognosis through delirium. Conclusion: The use of interventions to reduce delirium may improve patient prognosis. To improve the dependency activities and risk of pressure ulcers that directly affect delirium, early ambulation is encouraged, and treatment and nursing interventions to remove the ventilator and drainage tube quickly must be provided to minimize the application of restraint. Further, delirium can be prevented and patient prognosis improved through continuous intervention to stimulate cognitive awareness and monitoring of the onset of delirium. This study also discussed the effects of delirium intervention on the prognosis of patients with delirium and future research in this area.

• International Journal of Fluid Machinery and Systems
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• 제2권1호
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• pp.61-71
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• 2009

Machine fault diagnostic and prognostic techniques have been the considerable subjects of condition-based maintenance system in the recent time due to the potential advantages that could be gained from reducing downtime, decreasing maintenance costs, and increasing machine availability. For the past few years, research on machine fault diagnosis and prognosis has been developing rapidly. These publications covered in the wide range of statistical approaches to model-based approaches. With the aim of synthesizing and providing the information of these researches for researcher's community, this paper attempts to summarize and classify the recent published techniques in diagnosis and prognosis of rotating machinery. Furthermore, it also discusses the opportunities as well as the challenges for conducting advance research in the field of machine prognosis.

• Genomics & Informatics
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• 제16권4호
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• pp.32.1-32.7
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• 2018

Ovarian cancer is one of the leading causes of cancer-related deaths in gynecological malignancies. Over 70% of ovarian cancer cases are high-grade serous ovarian cancers and have high death rates due to their resistance to chemotherapy. Despite advances in surgical and pharmaceutical therapies, overall survival rates are not good, and making an accurate prediction of the prognosis is not easy because of the highly heterogeneous nature of ovarian cancer. To improve the patient's prognosis through proper treatment, we present a prognostic prediction model by integrating high-dimensional RNA sequencing data with their clinical data through the following steps: gene filtration, pre-screening, gene marker selection, integrated study of selected gene markers and prediction model building. These steps of the prognostic prediction model can be applied to other types of cancer besides ovarian cancer.

• The Journal of Advanced Prosthodontics
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• 제10권6호
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• pp.395-400
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• 2018

PURPOSE. This study tried to find the most significant factors predicting implant prognosis using machine learning methods. MATERIALS AND METHODS. The data used in this study was based on a systematic search of chart files at Seoul National University Bundang Hospital for one year. In this period, oral and maxillofacial surgeons inserted 667 implants in 198 patients after consultation with a prosthodontist. The traditional statistical methods were inappropriate in this study, which analyzed the data of a small sample size to find a factor affecting the prognosis. The machine learning methods were used in this study, since these methods have analyzing power for a small sample size and are able to find a new factor that has been unknown to have an effect on the result. A decision tree model and a support vector machine were used for the analysis. RESULTS. The results identified mesio-distal position of the inserted implant as the most significant factor determining its prognosis. Both of the machine learning methods, the decision tree model and support vector machine, yielded the similar results. CONCLUSION. Dental clinicians should be careful in locating implants in the patient's mouths, especially mesio-distally, to minimize the negative complications against implant survival.