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Hypertension Occurrence Analysis using a Bayesian Network
Junghye Lee(이정혜),Wonji Lee(이원지),Hyeseon Lee(이혜선),Chi-Hyuck Jun(전치혁) 대한산업공학회 2014 대한산업공학회 춘계학술대회논문집 Vol.2014 No.5
The Bayesian network (BN) is a useful method for modeling healthcare issues since a BN can graphically represent causal relationships among variables and provide its probabilistic information,. In this study, we apply a BN method to hypertension occurrence analysis. This study used the National Health Insurance Corporation (NHIC) database from 2002 to 2010 which contains more than 100,000 cases of personal medical examinations in Korea. We investigate the causality for hypertension occurrence by a structure learning step, and then evaluate the performance to predict hypertension occurrence through parameter learning and inference steps. It is shown that the BN outperforms other prediction methods such as logistic regression, naive Bayes and support vector machine in terms of sensitivity. In addition, the BN has advantages in interpreting which variables affect the hypertension occurrence and how they are related to each other.
Hypertension Occurrence Analysis using a Bayesian Network
Junghye Lee(이정혜),Wonji Lee(이원지),Hyeseon Lee(이혜선),Chi-Hyuck Jun(전치혁) 한국경영과학회 2014 한국경영과학회 학술대회논문집 Vol.2014 No.5
The Bayesian network (BN) is a useful method for modeling healthcare issues since a BN can graphically represent causal relationships among variables and provide its probabilistic information,. In this study, we apply a BN method to hypertension occurrence analysis. This study used the National Health Insurance Corporation (NHIC) database from 2002 to 2010 which contains more than 100,000 cases of personal medical examinations in Korea. We investigate the causality for hypertension occurrence by a structure learning step, and then evaluate the performance to predict hypertension occurrence through parameter learning and inference steps. It is shown that the BN outperforms other prediction methods such as logistic regression, naive Bayes and support vector machine in terms of sensitivity. In addition, the BN has advantages in interpreting which variables affect the hypertension occurrence and how they are related to each other.
Prediction of Hypertension Complications Risk Using Classification Techniques
Lee, Wonji,Lee, Junghye,Lee, Hyeseon,Jun, Chi-Hyuck,Park, Il-Su,Kang, Sung-Hong Korean Institute of Industrial Engineers 2014 Industrial Engineeering & Management Systems Vol.13 No.4
Chronic diseases including hypertension and its complications are major sources causing the national medical expenditures to increase. We aim to predict the risk of hypertension complications for hypertension patients, using the sample national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques, such as logistic regression, linear discriminant analysis, and classification and regression tree to predict the hypertension complication onset event for each patient. The performance of these three methods is compared in terms of accuracy, sensitivity and specificity. The result shows that these methods seem to perform similarly although the logistic regression performs marginally better than the others.
Perception of and attitude toward ethical issues among Korean occupational physicians
Junghye Choi,Chunhui Suh,Jong-Tae Lee,Segyeong Lee,Chae-Kwan Lee,Gyeong-Jin Lee,Taekjoong Kim,Byung-Chul Son,Jeong-Ho Kim,Kunhyung Kim,Dae Hwan Kim,Ji Young Ryu 대한직업환경의학회 2017 대한직업환경의학회지 Vol.29 No.-
Background: Occupational physicians (OPs) have complex relationships with employees, employers, and the general public. OPs may have simultaneous obligations towards third parties, which can lead to variable conflicts of interests. Among the various studies of ethical issues related to OPs, few have focused on the Korean OPs. The aim of the present survey was to investigate the ethical contexts, the practical resolutions, and the ethical principles for the Korean OPs. Methods: An email with a self-administered questionnaire was sent to members of the Korean Society of Occupational and Environmental Medicine, comprising 150 specialists and 130 residents. The questionnaire was also distributed to 52 specialists and 46 residents who attended the annual meeting of the Korean Association of Occupational and Environmental Clinics in October 2015, and to 240 specialists by uploading the questionnaire to the online community ‘oem-doctors’ in February 2016. The responses to each question (perception of general ethical conflicts, recognition of various ethical codes for OPs, core professional values in ethics of occupational medicine, and a mock case study) were compared between specialists and residents by the chi-squared test and Fisher’s exact test. Results: Responses were received from 80 specialists and 71 residents. Most participants had experienced ethical conflicts at work and felt the need for systematic education and training. OPs suffered the most ethical conflicts in decisions regarding occupational health examination and evaluation for work relatedness. Over 60% of total participants were unaware of the ethical codes of other countries. Participants thought ‘consideration of worker’s health and safety’ (26.0%) and ‘neutrality’ (24.7%) as the prominent ethical values in professionality ofoccupational medicine. In mock cases, participants chose beneficence and justice for fitness for work and confidential information acquired while on duty, and beneficence and respect for autonomy in pre-placement examinations. Conclusions: This study evaluated the current perception of and attitude toward ethical issues among the Korean OPs. These findings will facilitate the development of a code of ethics and the ethical decision-making program forthe Korean OPs.
Risk Prediction of Hypertension Complicates using Classification Techniques
Wonji Lee(이원지),Junghye Lee(이정혜),Hyeseon Lee(이혜선),Chi-Hyuck Jun(전치혁),Il-su Park 대한산업공학회 2014 대한산업공학회 춘계학술대회논문집 Vol.2014 No.5
A hypertension complications is one of the sources causing the national medical expenditures to increase. We aim to score the risk of hypertension complications for hypertension patients, using national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques such as logistic regression, linear discriminant analysis and classification and regression tree to score the risk of hypertension complication onset and also compare the performance of those methods. These three methods seem to perform similarly although the logistic regression performs better than others marginally. This study is meaningful in that the database used is a representative sample for the whole nation.
Prediction of Hypertension Complications Risk Using Classification Techniques
Wonji Lee,Junghye Lee,Hyeseon Lee,Chi-Hyuck Jun,Il-su Park,Sung-Hong Kang 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.4
Chronic diseases including hypertension and its complications are major sources causing the national medical expenditures to increase. We aim to predict the risk of hypertension complications for hypertension patients, using the sample national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques, such as logistic regression, linear discriminant analysis, and classification and regression tree to predict the hypertension complication onset event for each patient. The performance of these three methods is compared in terms of accuracy, sensitivity and specificity. The result shows that these methods seem to perform similarly although the logistic regression performs marginally better than the others.
Risk Prediction of Hypertension Complicates using Classification Techniques
Wonji Lee(이원지),Junghye Lee(이정혜),Hyeseon Lee(이혜선),Chi-Hyuck Jun(전치혁),Il-su Park 한국경영과학회 2014 한국경영과학회 학술대회논문집 Vol.2014 No.5
A hypertension complications is one of the sources causing the national medical expenditures to increase. We aim to score the risk of hypertension complications for hypertension patients, using national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques such as logistic regression, linear discriminant analysis and classification and regression tree to score the risk of hypertension complication onset and also compare the performance of those methods. These three methods seem to perform similarly although the logistic regression performs better than others marginally. This study is meaningful in that the database used is a representative sample for the whole nation.
Classification of High Dimensionality Data through Feature Selection Using Markov Blanket
Junghye Lee,Chi-Hyuck Jun 대한산업공학회 2015 Industrial Engineeering & Management Systems Vol.14 No.2
A classification task requires an exponentially growing amount of computation time and number of observations as the variable dimensionality increases. Thus, reducing the dimensionality of the data is essential when the number of observations is limited. Often, dimensionality reduction or feature selection leads to better classification performance than using the whole number of features. In this paper, we study the possibility of utilizing the Markov blanket discovery algorithm as a new feature selection method. The Markov blanket of a target variable is the minimal variable set for explaining the target variable on the basis of conditional independence of all the variables to be connected in a Bayesian network. We apply several Markov blanket discovery algorithms to some high-dimensional categorical and continuous data sets, and compare their classification performance with other feature selection methods using wellknown classifiers.