• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.529-538
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• 2018

Tuberculosis causes high morbidity and mortality. However, Korea still has the highest tuberculosis (TB) incidence and mortality among OECD countries despite decreasing incidence and mortality due to the development of modern medicine. Korea has now implemented various policy projects to prevent and control tuberculosis. This study analyzes the effects of public-private mix (PPM) tuberculosis control program on treatment outcomes and identifies the factors that affecting the success of TB treatment. We analyzed 130,000 new tuberculosis patient cohort from 2012 to 2015 using data of tuberculosis patient reports managed by the Disease Control Headquarters. A cumulative incidence function (CIF) compared the cumulative treatment success rates for each factor. We compared the results of the analysis using two popular types of competition risk models (cause-specific Cox's proportional hazards model and subdistribution hazard model) that account for the main event of interest (treatment success) and competing events (death).

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.302-310
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• 2022

Efficient use of limited blood products is becoming very important in terms of socioeconomic status and patient recovery. To predict the appropriateness of patient-specific transfusions for the intensive care unit (ICU) patients who require real-time monitoring, we evaluated a model to predict the possibility of transfusion dynamically by using the Medical Information Mart for Intensive Care III (MIMIC-III), an ICU admission record at Harvard Medical School. In this study, we developed an explainable machine learning to predict the possibility of red blood cell transfusion for major medical diseases in the ICU. Target disease groups that received packed red blood cell transfusions at high frequency were selected and 16,222 patients were finally extracted. The prediction model achieved an area under the ROC curve of 0.9070 and an F1-score of 0.8166 (LightGBM). To explain the performance of the machine learning model, feature importance analysis and a partial dependence plot were used. The results of our study can be used as basic data for recommendations related to the adequacy of blood transfusions and are expected to ultimately contribute to the recovery of patients and prevention of excessive consumption of blood products.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.299-306
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• 2020

The purpose of this study is to find out specific measures that can help the management strategy of patient-centered medical institutions by conducting research on patient experience surveys of convergence outpatient medical services using data mining techniques according to changes in patient-centered medical culture. Using the raw data of the 2018 Medical Service Experience Survey, 8,843 people over the age of 15 who had patient experience in outpatient medical services were analyzed. Decision tree analysis was performed. The determinants of satisfaction with outpatient medical services patient experience were the doctor's area and patient's rights protection area, and the determinants of intention to recommend outpatient medical services were the doctor's area and facilities comfort. Women evaluated the experience positively in overall satisfaction as compared to men, and those over the age of 60 positively evaluated the overall satisfaction and intention to recommend. It is significant that the outpatient experience decision-making model is presented, and that the doctor's area, patient's rights protection area, and facility comfort are important factors. Long-term research on the 'Medical Service Experience Survey' is needed, and research on the inpatient medical service experience is needed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.429-432
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• 2015

Radio Frequency (RF) coils in Magnetic Resonance Imaging (MRI) systems interact with a patient's tissues, resulting in the absorption of RF energy by the tissues. The presence of an electrically conducting medical implant may concentrate the RF energy and causes tissue heating near the implant devices. Here we present a novel design for a medical lead to reduce this undesired heating. Specific Absorption Rate (SAR), an indicator of heating, was calculated. Remcom XFdtd software was used to calculate the peak SAR distribution (1g and 10 g) in a realistic model of the human body. The model contained a medical lead that was exposed to RF magnetic fields at 64 MHz (1.5 T MRI), 128 MHz (3 T MRI) and 300 MHz (7 T MRI) using a model of an MR birdcage body coil. Our results demonstrate that, our proposed design of adding nails to the medical lead can significantly reduce the SAR for different MRI systems.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.867-870
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• 2014

Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) ependymoma data to identify predictive models and potential disparity in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ependymoma. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome ('brain and other nervous systems' specific death in yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of ependymoma death was computed for the predictors for comparison. Results: A total of 3,500 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 79.8 (82.3) months. Some 46% of the patients were female. The mean (S.D.) age was 34.4 (22.8) years. Age was the most predictive factor of outcome. Unknown grade demonstrated a 15% risk of cause specific death compared to 9% for grades I and II, and 36% for grades III and IV. A 5-tiered grade model (with a ROC area 0.48) was optimized to a 3-tiered model (with ROC area of 0.53). This ROC area tied for the second with that for surgery. African-American patients had 21.5% risk of death compared with 16.6% for the others. Some 72.7% of patient who did not get RT had cerebellar or spinal ependymoma. Patients undergoing surgery had 16.3% risk of death, as compared to 23.7% among those who did not have surgery. Conclusion: Grading ependymoma may dramatically improve modeling of data. RT is under used for cerebellum and spinal cord ependymoma and it may be a potential way to improve outcome.

• Health Policy and Management
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• v.31 no.4
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• pp.518-530
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• 2021

Background: This study examined the effect of having a usual source of care on the degree of patient-centered communication among persons with disability. The role of the usual source of care has been emphasized to improve patient experience, especially for patients with complex health conditions. Methods: This study used the 2017-2018 Korean Health Panel data, and the final study observations were 22,475 (20,806 people without disability and 1,669 people with disability). We applied generalized estimating equation model to show the effect of having a usual source of care on patient-centered communication, and subgroup analysis considering the types and severity of disabilities. Results: Persons who have disabilities, compared with ones without it, significantly had more usual sources of care (32.4% vs. 24.6%). By type of disability, persons with mental (51.4%), internal organ (43.8%), visual (37%), and physical disabilities (31.6%) had more usual sources of care than hearing/speech (26.6%), and developmental disabilities (18.6%). The average score of patient-centered communication was higher among who had a usual sources of care (3.2 vs. 2.7), and the regression analysis showed that having a usual sources of care was positively associated with higher patient-centered communication score (𝛽=0.476, p<0.05). However, the positive effects of usual sources of care was not observed among persons with severe hearing/speech, developmental, and mental disabilities. Conclusion: This study showed that role of patient-centered communication was limited in persons with severe hearing/speech disabilities, developmental, and mental disabilities. The education programs and supports are needed to improve communication skills between medical staff and persons with specific types of disabilities.

• Journal of Radiation Protection and Research
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• v.34 no.3
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• pp.95-101
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• 2009

Protective behavior of radiological technologists against radiation exposure is important to achieve reduction of the patient doses without compromising medical achievements. This study attempts to provide a basic model for the sophisticated intervention strategy that increases the level of the protective behavior of the technologists. The model was applied to real situations in Korea to demonstrate its utility. The results of this study are summarized as follows: First, the protective environment showed the highest relationship in the factors considered, r=0.637 (p<0.01). Secondly, the important factors were protective environment in environment characteristics, expectation for the protective behavior 0.228 (p<0.001), self-efficacy 0.142 (p<0.001), and attitude for the protective behavior 0.178 (p<0.001) in personal characteristics, and daily patient -0.112 (p<0.001) and number of the participation in the education session for the protective behavior 0.074 (p<0.05). Thirdly, the final protective behavior model by a path analysis method had direct influence on the attitude 0.171 (p<0.01) and environment 0.405 (p<0.01) for the protective behavior, self efficacy 0.122 (p<0.01), expectation for the protective behavior 0.16 (p<0.01), and self-efficacy in the specialty of projects 0.154 (p<0.01). The acceptance of the model determined by the absolute fit index (GFI), 0.969, and by the incremental fit index (CFI), 0.943, showed very significant levels. Value of $x^2$/df that is a factor applied to verify the acceptance of the model was 37, which implies that the result can be accepted in the desirable range. In addition, the parsimonious fit index configured by AGFI (0.890) and TLI (0.852) was also considered as a scale that accepts the model in practical applications. In case of the establishment of some specific intervention strategies based on the protective behavior model against harmful radiation effects proposed in this study, the strategy will provide an effective way to prevent medical harmful radiation effects that could cause severe injuries to people.

• Journal of Hospice and Palliative Care
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• v.20 no.1
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• pp.1-7
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• 2017

The paper describes The Narrative Communication Model of Hope Seeking Intervention developed by the authors as an approach to help clients to have individually specific hope experiences. The Model is founded upon the existential conceptualization of hope that views hope as subjective, unique experiences of meaning and processes. The Model has been developed based on the findings both in the literature and the authors' work on the nature of hope and hope experiences and integrating the concept of hope as subjective meanings and experiences, the processes of story-telling and the concept of narrative configuration as a way to engage in person-specific experiences, and person-centered communication. The results of the experiences with the application of the model in a study are used to clarify the model further. The Model incorporating story-telling and narrative construction through person-centered communication is identified in three components-the story-telling, the narrative intervention, and the communication components. These components are processed as an intervention to culminate into person-specific hope experiences in which active participation of clients as the story-teller and of interventionist as the communicative facilitator is required to produce narratives of hope with individual specific thematic plots that become the basis for hope experiences. The application of the Model has shown positive outcomes in clients with successful seeking of own hope experiences. The success of the Model application seems to depend upon interventionists' understanding of the model and the competency with the application of person-centered communication strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• BMB Reports
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• v.52 no.6
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• pp.349-359
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• 2019

After the first research declaring the generation of human induced pluripotent stem cells (hiPSCs) in 2007, several attempts have been made to model neurodegenerative disease in vitro during the past decade. Parkinson's disease (PD) is the second most common neurodegenerative disorder, which is mainly characterized by motor dysfunction. The formation of unique and filamentous inclusion bodies called Lewy bodies (LBs) is the hallmark of both PD and dementia with LBs. The key pathology in PD is generally considered to be the alpha-synuclein (${\alpha}$-syn) accumulation, although it is still controversial whether this protein aggregation is a cause or consequence of neurodegeneration. In the present work, the recently published researches which recapitulated the ${\alpha}$-syn aggregation phenomena in sporadic and familial PD hiPSC models were reviewed. Furthermore, the advantages and potentials of using patient-derived PD hiPSC with focus on ${\alpha}$-syn aggregation have been discussed.