• Asia pacific journal of information systems
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• v.16 no.2
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• pp.69-84
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• 2006

Importance of Today's diffusion of integrated hospital information systems is that various and huge amount of data is being accumulated in their database systems. Many researchers have studied utilizing such hospital data. While most researches were conducted mainly for medical diagnosis, there have been insufficient studies to develop medical care cost prediction model, especially using machine learning techniques. In this research, therefore, we built a medical care cost prediction model for cancer patients using CBR (Case-Based Reasoning), one of the machine learning techniques. Its performance was compared with those of Neural Networks and Decision Tree models. As a result of the experiment, the CBR prediction model was shown to be the best in general with respect to error rate and linearity between real values and predicted values. It is believed that the medical care cost prediction model can be utilized for the effective management of limited resources in hospitals.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.415-424
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• 2021

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.

• Korean journal of medical education
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• v.30 no.4
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• pp.359-364
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• 2018

Purpose: Learning physiological concepts and their practical applications in the appropriate contexts remains a great challenge for undergraduate medical students. Hence the present study aimed to analyze the learning experience of undergraduate medical students during an active learning process of 'preparation of models' depicting physiological concepts. Methods: A total of 13 groups, involving 55 undergraduate medical students with three to five individuals in each group, were involved in model preparation. A total of 13 models were exhibited by the students. The students shared their learning experiences as responses to an open-ended questionnaire. The students' responses were analyzed and generalized comments were generated. Results: Analysis of the results showed that the act of 'model preparation' improved concept understanding, retention of knowledge, analytical skills, and referral habits. Further, the process of 'model preparation' could satisfy all types of sensory modality learners. Conclusion: This novel active method of learning could be highly significant in students' understanding and learning physiology concepts. This approach could be incorporated in the traditional instructor-centered undergraduate medical curriculum as a way to innovate it.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.63-66
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• 2014

Managing electronic medical record is very difficult, because the currently electronic medical system is not designed standard that is uniform and proper. In this paper, in order to overcome this situation, we propose meta-data for the management of the electronic medical record as a single system. To this end, we first analyzed the research on electronic medical records and related standards. Second, we, on the basis of the analysis result, abstracted electronic medical record and entities related on electronic medical, and we designed an entity-relationship model. And finally, we have to complete the meta-data through the setting attributes in this entity-relationship model. Through this study, it was possible that we can complete metadata highly expressive medical records, and suggest an alternative for problem of current medical records systems.

• Health Policy and Management
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• v.28 no.4
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• pp.339-351
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• 2018

Background: The purpose of this study is to estimate empirically whether there is a difference in medical use among income groups, and if so, how much. This study applies econometric model to the most recent year of Korean Medical Panel, 2015. The model consists of outpatient service and inpatient service models. Methods: The probit model is applied to the model which indicate whether or not the medical care has been used. Two step estimation method using maximum likelihood estimation is applied to the models of outpatient visits, hospital days, and outpatient and inpatient out-of-pocket cost models, with disconnected selection problems. Results: The results show that there was the inequality favorable to the low income group in medical care use. However, after controlling basic medical needs, there were no inequities among income groups in the outpatient visit model and the model of probability of inpatient service use. However, there were inequities favorable to the upper income groups in the models of probability of outpatient service use and outpatient out-of-pocket cost and the models of the number of length of stay and inpatient out-of-pocket cost. In particular, it shows clearly how the difference in outpatient service and inpatient service utilizations by income groups when basic medical needs are controlled. Conclusion: This means that the income contributes significantly to the degree of inequality in outpatient and inpatient care services. Therefore, the existence of medical care use difference under the same medical needs among income groups is a problem in terms of equity of medical care use, so great efforts should be made to establish policies to improve equity among income groups.

• The Korean Journal of Health Service Management
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• v.13 no.3
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• pp.13-26
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• 2019

Objectives: To investigate whether medical institutions can prevent accidents by analyzing the root cause of a medical accident and identifying the tendencies. Methods: A total of 345 medical cases were used for the RCA(Root Cause Analysis). The root causes were classified using the SHELL model. The suitability of the model was confirmed by SPSS's MDPREF and Euclidean distance. An SPSS20.0 hierarchical regression analysis was used as an influencing factor on the degree of injury resulting from medical accidents. Results: The SHELL model was suitable for classification. The rates of accident causes were LS49%, L34%, LL10.2%, LE3.7%, LH2.3%. The order in which the degree of a patient's injury was affected were: Risk Threshold (${\beta}=.180$), Time (${\beta}=.175$), Surgical stage (${\beta}=-.166$), Do not use procedure (${\beta}=.147$). Conclusions: Health care institutions should remove priorities through system improvement and training. For patients' safety, the five factors of the SHELL model should be managed in harmony.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7923-7927
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• 2015

Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.43-55
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• 2017

The market for medical tourism services in the world is steadily increasing and the medical tourism market in the South Korea is also showing high growth. However, they have also problem such as informal various information and services, irregularity price competition etc. In order to solve this problem, We have designed a medical tourism service model based on ICT specific on domestic medical ecosystem. First, analysis trends of domestic and overseas medical ecosystem and identify current problem of medical tourism. In order to solve existed problem we also have designed a medical tourism strategy. Based on the strategy, we have designed business service model based on ICT platform for as fit as Korea medical tourism status. The proposed medical tourism business service model can provide usability to customer and also can solve current medical tourism problem. We expect industrial effect and contribution to the activation.

• Korea Trade Review
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• v.45 no.1
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• pp.279-300
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• 2020

The cosmetic medical information mobile platform is evolving into a new channel for searching and obtaining relevant information before using cosmetic medical service. In addition, the medical institutions can facilitate the medical contracts, and take advantage of systemic customer management through the cosmetic medical information mobile platform. Therefore, the paradigm of the cosmetic medical mobile service industry is facing a flow of change through the use diffusion of cosmetic medical information mobile platform. In this study, in order to explore the factors affecting the use diffusion of the cosmetic medical information mobile platform, this study used the research model of the influence of the characteristics of the cosmetic medical information mobile platform on perceived convenience and usefulness, and use diffusion by applying TAM(Technology Acceptance Model). As a result, immediateness, interactivity, and customization in the characteristics of cosmetic medical information mobile platform had positive effects on the perceived convenience. Also, interactivity, customization, and economics had positive impacts on perceived usefulness. In addition, perceived convenience and usefulness had positive effects on the use diffusion. Through this study, the factors influencing the use diffusion of cosmetic medical information mobile platform were actually explored, and the service value of the cosmetic medical information mobile platform were categorized. Future research is expected to contribute to the continuous improvement of quality and expansion of the cosmetic medical service market based on various research.

• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.457-467
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• 2000

In this paper, we propose the method to extract the anatomical objects in medical images using active contour models and genetic algorithms. The performance of active contour models is mostly decided by the optimization of active contour model's energy. So, we propose to use genetic algorithms to optimize the energy of active contour models. We experimented our proposed method on the femoral head medical images and proved that our method provides very acceptable results from any initialization of active contour models.