• Tuberculosis and Respiratory Diseases
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• v.80 no.3
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• pp.230-240
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• 2017

Chronic obstructive pulmonary disease (COPD) results in high morbidity and mortality among patients both domestically and globally. The Korean clinical practice guideline for COPD was revised in 2014. It was drafted by the members of the Korean Academy of Tuberculosis and Respiratory Diseases, as well as participating members of the Health Insurance Review and Assessment Service, Korean Physicians' Association, and Korea Respiration Trouble Association. This revised guideline covers a wide range of topics, including the epidemiology, diagnosis, assessment, monitoring, management, exacerbation, and comorbidities of COPD in Korea. We drafted a guideline on COPD management by performing systematic reviews on the topic of management with the help of a meta-analysis expert. We expect this guideline will be helpful medical doctors treating patients with respiratory conditions, other health care professionals, and government personnel in South Korea.

• Journal of Biomedical Engineering Research
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• v.37 no.5
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• pp.178-185
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• 2016

Tear is a promising biological fluid for non-invasive health monitoring. It has been studied in the past to be a possible candidate for the diagnosis of certain systemic diseases, such as breast cancer, multiple sclerosis, prostate cancer, and diabetes. However, currently existing methods for collecting and extracting tear from the human eye causes inconsistencies in the biomolecule concentrations of the tear sample due to the irritating nature of the process. In response, we designed and fabricated a microfluidic system embedded soft contact-lens for the purpose of tear sampling. The lens was then tested with artificial tear for its tear sampling capability, and found to be able to find concentration equilibrium within 50 minutes. Additionally, simulation was carried out to further optimize the design so that tear sampling rate matched the natural tear turn-over rate of 1 microliter per minute.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.689-709
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• 2010

In this paper, a low cost, low power but multifunctional wireless sensor node is presented for the impedance-based SHM using piezoelectric sensors. Firstly, a miniaturized impedance measuring chip device is utilized for low cost and low power structural excitation/sensing. Then, structural damage detection/sensor self-diagnosis algorithms are embedded on the on-board microcontroller. This sensor node uses the power harvested from the solar energy to measure and analyze the impedance data. Simultaneously it monitors temperature on the structure near the piezoelectric sensor and battery power consumption. The wireless sensor node is based on the TinyOS platform for operation, and users can take MATLAB$^{(R)}$ interface for the control of the sensor node through serial communication. In order to validate the performance of this multifunctional wireless impedance sensor node, a series of experimental studies have been carried out for detecting loose bolts and crack damages on lab-scale steel structural members as well as on real steel bridge and building structures. It has been found that the proposed sensor nodes can be effectively used for local wireless health monitoring of structural components and for constructing a low-cost and multifunctional SHM system as "place and forget" wireless sensors.

• Smart Structures and Systems
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• v.33 no.3
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• pp.227-241
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• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2512-2545
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• 2024

One of the biggest challenges for the medical professionals is spotting cardiovascular issues in the earliest stages. Around the world, Cardiovascular Diseases (CVD) are a major cause of death for almost 18 million people each year. Heart disease is therefore a serious concern that needs to be treated. The numerous elements that affect health, such as excessive blood pressure, elevated cholesterol, aberrant pulse rate, and many other factors, might make it challenging to detect heart disease. Consequently, early disease detection and the development of effective treatments can benefit greatly from the field of artificial intelligence. The purpose of this work is to develop a new IoT based healthcare monitoring framework for the prediction of CVD using machine learning algorithm. Here, the data preprocessing has been performed to create the normalized dataset for improving classification. Then, an Artificial Gorilla Troop Optimization (AGTO) algorithm is deployed to choose the most pertinent features from the normalized dataset. Moreover, the Multi-Linear Regression Classification (MLRC) model is also implemented for accurately categorizing the medical information as whether healthy or CVD affected. The results of the proposed AGTO-MLRC mechanism is validated and compared using the popular benchmarking datasets.

• Journal of Genetic Medicine
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• v.4 no.1
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• pp.1-5
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• 2007

Unprecedented amount of genetic information being generated from the result of Human Genome Project (HGP) and advances in genetic research is already forcing changes in the paradigm of health and disease. The ultimate goal of genetic medicine is to use genetic information and technology to develop new ways of treatment or even prevention of the disease on an individual level for 'personalized medicine'. Genetics is play ing an increasingly important role in the diagnosis, monitoring and management of common multifactorial diseases in addition to rare single-gene disorders. While wide range of genetic testing have provided benefits to patients and family, uncertainties surrounding test interpretation, the current lack of available medical options for the diseases, and risks for discrimination and social stigmatization may remain to be resolved. However an increasing number of genetic tests are becoming commercially available, including direct to consumer genetic testing, yet public is often unaw are of their clinical and social implications. The personal nature of information generated by a genetic test, its power to affect major life decisions and family members, and its potential misuse raise important ethical considerations. Therefore appropriate genetic counseling is needed for patient to be informed with the benefits, limitations and risks of genetic tests, prior to informed consent for the tests. Physician also should be familiar with the legal and ethical issues involved in genetic testing to tell patients how w ell a particular genetic risk factor relates with likelihood of disease, and be able to provide appropriate genetic counseling. Genetic counseling become a mandatory requirement as global standard for many genetic testing such as prenatal diagnosis, presymtomatic DNA diagnostic tests and cancer susceptibility gene test for familial cancer syndrome. In oder to meet the challenge of genetic medicine of 21 century in korean health care system, professional education program and certification board for medical genetics specialist including non-MD genetic counselors should be addressed by medical society and regulatory policy of national health insurance reimbursement for genetic counseling to be in place to promote the implementation of clinical genetic service including genetic counseling for proper genetic testing.

• Korea Journal of Hospital Management
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• v.29 no.1
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• pp.1-18
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• 2024

Purposes: The Common Data Model(CDM) is very important for multi-institutional research. There are various domestic and international CDM construction cases to actively utilize it. In order to construct a CDM, different terms from each institution must be mapped to standard terms. Therefore, we intend to derive the importance and major issues of terminology mapping and propose a solution in CDM construction. Methodology/Approach: This study conducted terminology mapping between Electronic Health Record(EHR) and MOA CDM for constructing Medical Record Observation & Assessment for Drug Safety(MOA) CDM at Dankook University Hospital in 2022. In the process of terminology mapping, a CDM standard terminology process and method were developed and terminology mapping was performed by applying this. The constructions of CDM mapping terms proceeded in the order of diagnosis, drug, measurement, and treatment_procedure. Findings: We developed mapping guideline for CDM construction and used this for mapping. A total of 670,993 EHR data from Dankook University Hospital(January 1, 2013 to December 31, 2021) were mapped. In the case of diagnosis terminology, 19,413 were completely mapped. Drug terminology mapped 92.1% of 2,795. Measurement terminology mapped 94.5% of 7,254 cases. Treatment and procedure were mapped to 2,181 cases, which are the number of mapping targets. Practical Implications: This study found the importance of constructing MOA CDM for drug side effect monitoring and developed terminology mapping guideline. Our results would be useful for all future researchers who are conducting terminology mapping when constructing CDM.

• Smart Structures and Systems
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• v.33 no.4
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• pp.313-323
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• 2024

Deterioration of buildings is one of the biggest problems in modern society, and the importance of a safety diagnosis for old buildings is increasing. Therefore, most countries have legal maintenance and safety diagnosis regulations. However, the reliability of the existing safety diagnostic processes is reduced because they involve subjective judgments in the data collection. In addition, unstructured tasks increase rework rates, which are time-consuming and not cost-effective. Therefore, This paper proposed the method that can calculate the safety grade of deterioration automatically. For this, a DNN structure is generated by using existing precision inspection data and precision safety diagnostic data, and an objective building safety grade is calculated by applying status evaluation data obtained with a UAV, a laser scanner, and reverse engineering 3D models. This automated process is applied to 20 old buildings, taking about 40% less time than needed for a safety diagnosis from the existing manual operation based on the same building area. Subsequently, this study compares the resulting value for the safety grade with the already existing value to verify the accuracy of the grade calculation process, constructing the DNN with high accuracy at about 90%. This is expected to improve the reliability of aging buildings in the future, saving money and time compared to existing technologies, improving economic efficiency.

• Research in Community and Public Health Nursing
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• v.18 no.1
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• pp.165-176
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• 2007

Purpose: The purpose of this study was to investigate the needs of home care nursing services in relation to the patients in hospital. Method: Subjects were 129 patients who admitted hospital and were selected through convenience sampling. Data were collected using the Home Health Care Need Assessment Questionnaire constructed by the Korea Health Industry Development Institute. Data were analyzed using SAS 8.12 program by applying percentage. Results: 1. According to the diagnosis of the subjects, the majority had cancer (25.0%), followed by musculoskeletal disease (15,6%), neuro/cerebral vascular disease (14.1%), digestive (10.9%) and respiratory disease (10.9%). 2. With regard to fundamental nursing service, subjects wanted to receive home care services for the following reasons: Problem identification and diagnosis (77.5%), vital sign check (49.6%); and intake and output measure (20.9%). 3. With regard to clinical laboratory tests, 62.8% wanted to receive blood tests, and followed by urine tests 26.4%, and wound drainage 26.4%. 4. With regard to medication and treatment service, 40.3% of the subjects wanted to receive intravenous fluid therapy, 26.4% intravenous antibiotics, and 26.4% the monitoring of fluid therapy. 5. With regard to therapeutic nursing service, 33.3% wanted to receive wound care, 26.4% ROM exercise, and 27.9% foley catheter change and care. 6. With regard to educational needs, 42.6% wanted education on infection monitoring, 41.4% on medication, and 34.9% on diet. 7. With regard to counseling needs, 65.9% wanted to receive telephone counseling about patient condition, 52.7% counseling about re-admission and 51.9% direct counseling about patient condition. In the group of injury and toxicity, and cardiovascular/circulatory diseases, 100% wanted telephone and direct counseling about the patient condition. Conclusion: Therefore, in order to improve the quality of hospital based home health care services, various factors that affect to the need of home health care should be analyzed and specified nursing care should be looked into.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.34-42
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• 2009

Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.