• Asian Pacific Journal of Cancer Prevention
• /
• 제17권3호
• /
• pp.1261-1264
• /
• 2016

Background: In breast cancer (BC), it has been suggested that nuclear overexpression of p53 protein might be an indicator of poor prognosis. The aim of the current study was to evaluate the expression of p53 BC in Kurdish women from the West of Iran and its correlation with other clinicopathology figures. Materials and Methods: In the present retrospective study, 231 patients were investigated for estrogen receptor (ER) and progesterone receptor (PR) positivity, defined as ${\geq}10%$ positive tumor cells with nuclear staining. A binary logistic regression model was selected using Akaike Information Criteria (AIC) in stepwise selection for determination of important factors. Results: ER, PR, the human epidermal growth factor receptor 2 (HER2) and p53 were positive in 58.4%, 55.4%, 59.7% and 45% of cases, respectively. Ki67 index was divided into two groups: 54.5% had Ki67<20% and 45.5% had Ki67 ${\geq}20%$. Of 214 patients, 137(64%) had lymph node metastasis and of 186 patients, 122(65.6%) had vascular invasion. Binary logistic regression analysis showed that there was inverse significant correlation between lymph node metastasis (P=0.008, OR 0.120 and 95%CI 0.025-0.574), ER status (P=0.006, OR 0.080, 95%CI 0.014-0.477) and a direct correlation between HER2 (P=005, OR 3.047, 95%CI 1.407-6.599) with the expression of p53. Conclusions: As in a number of studies, expression of p53 had a inverse correlation with lymph node metastasis and ER status and also a direct correlation with HER2 status. Also, p53-positivity is more likely in triple negative BC compared to other subtypes.

• 한국ITS학회 논문지
• /
• 제22권4호
• /
• pp.114-131
• /
• 2023

개인형 이동수단의 이용이 활성화됨에 따라, 관련한 PM 사고도 급격하게 증가하였다. 이러한 사고 증가에 대응하기 위해, 2021년 5월 13일 정부에서는 관련 규정을 강화하였지만, PM 가해사고의 증가 추이는 피해사고의 증가 추이보다 크게 감소하지 않았다. 이러한 PM 가해사고의 대부분은 보행자와의 충돌 사고로, 보행자들의 안전이 위협받고 있는 것을 알 수 있었다. 이에 본 연구에서는 PM 대 보행자 충돌사고를 중점적으로 규제 및 기상환경, 도시건조환경 특성 등을 반영하여, PM 대 보행자 교통사고 심각도에 영향을 미치는 요인들을 분석하였다. 2020년부터 2021년 간 서울시에서 발생한 PM 대 보행자 교통사고를 수집하였으며, 이항 로지스틱 회귀분석을 활용하여 분석을 수행하였다. 주요 분석결과를 통해 정책적 시사점을 도출하였다.

• 운동영양학회지
• /
• 제14권2호
• /
• pp.81-86
• /
• 2010

The purpose of this study was to identify the factors associated with child's Body Mass Index (BMI) and physical activity. The participants (n = 133) were Korean juveniles (3^rd and 4^th graders) and their parents. They completed a questionnaire packet including the SPARK (Sports, Play, and Active Recreation for Kids) survey and the parent equivalent survey. Correlation, multiple linear regression and binary logistic regression analyses were applied to identify the association between child's BMI and 10 factors of SPARK as predict or variables. 25.6% of the participants were classified as overweight (21.1%) or obesity (4.5%). 3 parental factors including mother's BMI and frequency of mother's and father's physical activity were identified as significant predictors of children's BMI. The 10 variables accounted for 28% of the variance (p<.01) in the linear regression model. These results provide insight into parental factors which are related to a child's BMI and physical activity. Parental role modeling which refers to parents' efforts to model an active lifestyle for children plays an important role.

• Communications for Statistical Applications and Methods
• /
• 제29권5호
• /
• pp.499-512
• /
• 2022

Intervention measures have been implemented worldwide to reduce the spread of the COVID-19 outbreak. The COVID-19 outbreak has occured in several waves of infection, so this paper is divided into three groups, namely those countries who have passed the pandemic period, those countries who are still experiencing a single-wave pandemic, and those countries who are experiencing a multi-wave pandemic. The purpose of this study is to develop a multi-wave Richards model with several changepoint detection methods so as to obtain more accurate prediction results, especially for the multi-wave case. We investigated epidemiological trends in different countries from January 2020 to October 2021 to determine the temporal changes during the epidemic with respect to the intervention strategy used. In this article, we adjust the daily cumulative epidemiological data for COVID-19 using the logistic growth model and the multi-wave Richards curve development model. The changepoint detection methods used include the interpolation method, the Pruned Exact Linear Time (PELT) method, and the Binary Segmentation (BS) method. The results of the analysis using 9 countries show that the Richards model development can be used to analyze multi-wave data using changepoint detection so that the initial data used for prediction on the last wave can be determined precisely. The changepoint used is the coincident changepoint generated by the PELT and BS methods. The interpolation method is only used to find out how many pandemic waves have occurred in given a country. Several waves have been identified and can better describe the data. Our results can find the peak of the pandemic and when it will end in each country, both for a single-wave pandemic and a multi-wave pandemic.

• 대한한의학회지
• /
• 제40권4호
• /
• pp.49-60
• /
• 2019

Objectives: To develop a standardized diagnostic pattern identification equation for stroke patients, our group conducted a study to derive the predictive logistic equations. However, the sample size was relatively small. In the current study, we aimed to derive new predictive logistic equations for each diagnostic pattern using an expanded number of subjects. Methods: This study was a hospital-based multi-center trial recruited stroke patients within 30 days of symptom onset. Patients' general information, and the variables related to diagnostic pattern identification were measured. The diagnostic pattern of each patient was identified independently by two Korean Medicine Doctors. To derive a predictive model for pattern identification, binary logistic regression analysis was applied. Results: Among the 1,251 patients, 385 patients (30.8%) had the Fire Heat Pattern, 460 patients (36.8%) the Phlegm Dampness Pattern, 212 patients (16.9%) the Qi Deficiency Pattern, and 194 patients (15.5%) the Yin Deficiency Pattern. After the regression analysis, the predictive logistic equations for each pattern were determined. Conclusion: The predictive equations for Fire Heat, Phlegm Dampness, Qi Deficiency, and Yin Deficiency would be useful to determine individual stroke patients' pattern identification in the clinical setting. However, further studies using objective measurements are necessary to validate these data.

• 정보기술응용연구
• /
• 제1권
• /
• pp.173-211
• /
• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• 한국항행학회논문지
• /
• 제17권6호
• /
• pp.652-657
• /
• 2013

논문에서는 두 가지 혼돈맵들을 연결시킨 하나의 합성맵을 기초로 사용하는 독립된 하나의 합성상태머신을 설계하는 방법 및 그 결과를 제시하였다. 혼돈2진스트림발생기로 사용하기 위하여 혼돈합성맵에 관한 디지털회로를 설계하였다. 두 가지 혼돈함수들- 톱니함수와 비뚤어진 로지스틱 함수-로 구성되는 혼돈합성함수의 이산화 진리표를 작성하였고, 디지털회로의 수학적 모델로써 간략화 된 부울대수식들을 제시하였다. 결과로써 혼돈합성함수의 맵에 관한 디지털회로들을 제시하였다.

• 문화기술의 융합
• /
• 제6권3호
• /
• pp.457-462
• /
• 2020

골다공증은 주로 노인에서 나타나는 질병으로써 뼈 질량 및 조직의 구조적 악화에 따라 골절의 위험을 증가시킨다. 본 연구의 목적은 영양소 성분과 골다공증과의 연관성을 파악하고, 영양소 성분을 기반으로 골다공증을 예측하는 모델을 생성 및 평가하는 것이다. 실험방법으로 binary logistic regression을 이용하여 연관성분석을 수행하였고, naive Bayes 알고리즘과 variable subset selection 메소드를 이용하여 예측 모델을 생성하였다. 단일 변수들에 대한 분석결과는 남성에서 식품섭취량과 비타민 B2가 골다공증을 예측하는데 가장 높은 the area under the receiver operating characteristic curve (AUC)값을 나타내었다. 여성에서는 단일불포화지방산이 가장 높은 AUC값을 나타내었다. 여성 골다공증 예측모델에서는 Correlation based feature subset 및 wrapper 기반 feature subset 메소드를 이용하여 생성된 모델이 0.662의 AUC 값을 얻었다. 남성에서 전체변수를 이용한 모델은 0.626의 AUC를 얻었고, 그외 남성 모델들에서는 민감도와 1-특이도에서 예측 성능이 매우 낮았다. 이러한 연구결과는 향후 골다공증 치료 및 예방을 위한 기반정보로 활용할수 있을 것으로 기대된다.

• Journal of the Korean Data and Information Science Society
• /
• 제15권3호
• /
• pp.565-574
• /
• 2004

Classification tree algorithms including as CART by Brieman et al.(1984) in some aspects, recursively partition the data space with the aim of making the distribution of the class variable as pure as within each partition and consist of several steps. SUPPORT(smoothed and unsmoothed piecewise-polynomial regression trees) method of Chaudhuri et al(1994), a weighted averaging technique is used to combine piecewise polynomial fits into a smooth one. We focus on applying SUPPORT to a binary class variable. Logistic model is considered in the caculation techniques and the results are shown good classification rates compared with other methods as CART, QUEST, and CHAID.

• 한국항행학회논문지
• /
• 제17권3호
• /
• pp.292-297
• /
• 2013

본 논문에서는 혼돈 스트림 발생기에 사용되는 혼돈합성함수의 디지털 회로설계를 연구 하였다. 혼돈키 스트림 발생기의 수학적 모델에 기인하는 전반적인 설계 개념과 절차를 자세히 설명하였다. 또한 혼돈 함수에 대한 이진화 2진 진리표를 보였다. 결과로서 1차원과 2차원 두 종류의 혼돈맵들-텐트맵과 삐뚤어진 로지스틱 맵-을 연결시켜 합성맵으로 사용하는 합성상태머신의 설계를 제시하였다.