• Genomics & Informatics
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• v.7 no.3
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• pp.159-162
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• 2009

Human personal genome sequencing can be done with high efficiency by aligning a huge number of short reads derived from various next generation sequencing (NGS) technologies to the reference genome sequence. One of the major obstacles is the incompleteness of human reference genome. We tried to analyze the effect of hidden gene duplication on the NGS data using the known example of hydin gene. Hydin2, a duplicated copy of hydin on chromosome 16q22, has been recently found to be localized to chromosome 1q21, and is not included in the current version of standard human genome reference. We found that all of eight personal genome data published so far do not contain hydin2, and there is large number of nsSNPs in hydin. The heterozygosity of those nsSNPs was significantly higher than expected. The sequence coverage depth in hydin gene was about two fold of average depth. We believe that these unique finding of hydin can be used as useful indicators to discover new hidden multiplication in human genome.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.149-156
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• 2020

In the Fourth Industrial Revolution, successful cases using big data in various industries are reported. This paper examines cases that successfully use big data in the medical industry to develop the service and draws implications in value that big data create. The related work introduces big data technology in the medical field and cases of eight innovative service in the big data service are explained. In the introduction, the overall structure of the study is mentioned by describing the background and direction of this study. In the literature study, we explain the definition and concept of big data, and the use of big data in the medical industry. Next, this study describes the several cases, such as technologies using national health information and personal genetic information for the study of diseases, personal health services using personal biometric information, use of medical data for efficiency of business processes, and medical big data for the development of new medicines. In the conclusion, we intend to provide direction for the academic and business implications of this study, as well as how the results of the study can help the domestic medical industry.

• Journal of the Korean housing association
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• v.19 no.5
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• pp.57-65
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• 2008

The purpose of this study is to figure out the relationship between the residence stories in high-rise condominium and residents' disease patterns throughout the dweller's medical reports. Research basic data are obtained from medical fee request of National Health Insurance Corporation. Data are limited to 'A' high-rise condominium and a medical treatment time to 3 years (2004. 1-2006, 12). Data for analysis are composed of total 346,286 medical records, 43,159 disease records, and 8,999 personal records. Data are stored by sex, age, building story, residence story, visiting year and month, treatment days, main disease type (KCD-4). Treatment number, disease type and asthma in disease records and personal records are statistically analyzed by residence story considering age. Findings are as follows: 1) Women have more medical treatments than men, 40-50 age group is more treated, and the residents of 6-25 stories are more received medical treatments. According to KCD-4, diseases of the respiratory system and diseases of the eye and adnexa are relatively treated higher than other diseases. 2) The diseases of he respiratory system, the eye and adnexa, the skin and subcutaneous issue, the ear and mastoid process, and the asthma have not relation to the high-storied residence through the data of disease records and personal records. But the analysis on the data of children, age 7 and less, showed a significant relation. to conclude, there is no relationship between the residence of high-stories in the condominium and residents' disease patterns, but there is a little probable to the relationship in the pre-school child.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.303-308
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• 2017

Nowadays, living standard is improved and people have high interest to the personal health care problem. Accordingly, people desire to know the personal physical condition and the related medical treatment. Thus, there is the necessary of the personalized medical treatment, and there are many studies about the automatic disease diagnosis and the related services. Those studies focus on the particular disease prediction which is based on the related particular data. However, there is no studies about the medical treatment prediction. In our study, national health data based medical treatment predictor is built by using SVM, and the performance is evaluated by comparing with other prediction methods. The experimental results show that the health data based medical treatment prediction resulted in the average accuracy of 80%, and the SVM performs better than other prediction algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4400-4419
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• 2021

In the 4th Industrial Revolution, the healthcare industry is undergoing a paradigm shift from post-care and management systems based on diagnosis and treatment to disease prevention and management based on personal precision medicine. To optimize medical services for individual patients, an open ecosystem for the healthcare industry that allows the exchange and utilization of personal health records (PHRs) is required. However, under the current system of hospital-centered data management, it is difficult to implement the linking and sharing of PHRs in practice. To address this problem, in this study, we present the design and implementation of a patient-centered PHR platform using blockchain technology. This platform achieved transparency and reliability in information management by eliminating the risk of leakage and tampering/altering personal information, which could occur when using a PHR. In addition, the patient-consent system was applied to a PHR; thus, the patient acted as the user with ownership. The proposed blockchain-based PHR platform enables the integration of personal medical information with scattered distribution across multiple hospitals, and allows patients to freely use their health records in their daily lives and emergencies. The proposed platform is expected to serve as a stepping stone for patient-centered healthcare data management and utilization.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.18-23
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• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.268-275
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• 2014

In future, hospitals are expected to automatically issue remote transcriptions. Many general hospitals are planning to encrypt their medical database to secure personal information as mandated by law. The electronic medical record system, picture archiving communication system, and the clinical data warehouse, amongst others, are the preferred targets for which stronger security is planned. In the near future, medical systems can be assumed to be automated and connected to remote locations, such as rural areas, and islands. Connecting patients who are in remote locations to medical complexes that are usually based in larger cities requires not only automatic processing, but also a certain amount of security in terms of medical data that is of a sensitive and critical nature. Unauthorized access to patients' transcription data could result in the data being modified, with possible lethal results. Hence, personal and sensitive data on telemedicine and medical information systems should be encrypted to protect patients from these risks. Login passwords, personal identification information, and biological information should similarly be protected in a systematic way. This paper proposes the use of electronic acupuncture with a built-in multi-pad, which has the advantage of being able to establish a patient's physical condition, while simultaneously treating the patient with acupuncture. This system implements a sensing pad, amplifier, a small signal drive circuit, and a digital signal processing system, while the use of a built-in fuzzy technique and a control algorithm have been proposed for performing analyses.

• Journal of Trauma and Injury
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• v.31 no.3
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• pp.125-134
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• 2018

Purpose: The interest in the personal mobility started to grow and as the interest increases, there are growing concerns about the safety of it. The purpose of the study is to look at the types and dynamics of patients injured by the personal mobilities. Methods: This was a retrospective 2-year observational study, from January 2016 to December 2017, on the patients who visited the emergency center and the trauma center, with an injury related to driving the personal mobility. Cases of the personal mobility-related accident were collected based on electronic medical records and hospital emergency department-based injury in-depth surveillance data. Results: A total of 65 patients visited the emergency center and the trauma center, during this study period. Six patients of 50 adults admitted the alcohol consumption (12%) and two adult patients wore the helmet as the protection gear (3.1%). The number of the patients in 2017 rises three times more than the number of patients in 2016 (51 vs. 14). Injuries to the head and neck region (67.7%) was the most common, followed by the upper extremity (46.2%). Eleven patients (16.9%) were admitted to the hospital, of whom three were admitted to the intensive care unit due to intracranial hemorrhage. Nine patients underwent surgery. Conclusions: The use of the personal mobility will continue to grow and the accidents, caused by the vehicle, will increase along with it. The study showed the damage is worse than expected. Personal mobility currently has a limited safety laws and the riders are not yet fully aware of its danger. The improvement of the regulation of the personal mobility, safety education is needed.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.395-411
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• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

• Korean Journal of Adult Nursing
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• v.26 no.5
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• pp.500-511
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• 2014

Purpose: The purpose of this study was to investigate predictors of violent behavior by patient or caregiver of patient in the emergency department. Methods: Subjects of the study were 447 residents who have visited the emergency department in community P Metropolitan City during the past year. The data collecting period was from June 1, 2012 to August 31, 2012. Data was collected using self-reported questionnaires. Results: Predictors of violent behavior in the emergency department were divided into personal and institutional factors. Personal factors included relationship with patients, presence of alcohol, reports of discontent during and past treatment and responses to deterioration in patient's conditions, institution factors included perceived attitudes toward medical workers' explanations and proficiency of medical workers, and delay in medical treatment hours. Conclusion: Knowledge of personal and institutional factors may permit emergency staff to minimize or prevent potential violence in the emergency department.