• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.947-971
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• 2022

The Electronic Medical Record (EMR) is a valuable source of medical data intelligence in e-health systems. The watermarking techniques have been used to authenticate the owner and protect the EMR from illegal copying. The existing distributive strategies, successfully operated to secure the EMR, are found to be inadequate. Blockchain technology, mainly, is employed by a sharing database that allows the digital crypto-currency. It rapidly leads to the magnified expectations acme. In this excitement, the use of consortium adopting the technology based on Blockchain, in the EMR structure, is found improving. This type of consortium adds an immutable share with a translucent record of the entire business and it is accomplished with responsibility, along with faith and transparency. The combination of watermarking and Blockchain technology provides a singular chance to promote a secured, trustworthy electronic documents administration to share with the e-records system. The authors, in this article, present their views on consortium Blockchain technology which is incorporated in the EMR system. The ledger, used for the distribution of the block structure, has team healthcare models based on dissimilar multiple image watermarking techniques.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.300-306
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• 2011

In this paper, we suggest a usage profiles for electric home appliances. In Korea, it is published the records for total consumption of electricity in a house but the electric home appliance consumption records in a households are not. To build the data, we must collect the usage of every appliances in a house and the information of the household which live in the house. Unfortunately, it is hard to get the data because of the worry about the breach of privacy. In this paper, we make a scenarios on the electricity consumption pattern of a few households type. Based on the conjecture, we make the power consumption profiles for some home appliances. Comparison to the total electric consumption records for a house, we found our scenarios are quite reasonable.

• The Korean Society of Law and Medicine
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• v.7 no.1
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• pp.323-386
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• 2006

A combination of information technology and medical care has given rise to a new type of medicine, i.e., telemedicine. Broadly defined, telemedicine is the transfer of electronic medical data from one location to another. Both at home and abroad, telemedicine has come to success in establishing appropriate equipment and solutions for such non-conventional medicine. Sooner or later, telemedicine is believed to find itself as one of the universal treatments. In order to facilitate the full-fledged development of telemedicine, a number of legal and institutional problems have to be settled. In Korea, the Medical Act was amended to include such provisions as telemedicine, electronic medical records, electronic prescriptions, etc. and the Act came into force on March 31, 2002. Telemedicine is in common with the conventional medicine in that a physician treats a patient. However, telemedicine is basically differentiated in the followings: - The offer and acceptance of treatment and medication are usually made on-line; - Telemedicine is inherently dangerous because a physician cannot meet face-to-face with a patient; and - Joint and several liability is borne by all the physicians involved in a telemedical consultation. As a result, telemedicine is vulnerable in nature to medical malpractice. Accordingly, there must be some new theories and arguments in the formation of contract and torts. The discussion on the civil liability covers the above-mentioned issues, and would give an insight or guidelines in the concerted operation of provisions with respect to telemedicine. This study delves into the civil liability of physicians involved in telemedical consultations and treatments based upon the conventional malpractice theory.

• Journal of Korean Society of Archives and Records Management
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• v.10 no.1
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• pp.169-197
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• 2010

The purpose of this study is to propose a different classification method for keeping a record of cases. After proving that criminal case files should be counted as one type of case files, based on their characteristics and characteristics, this research analyzes the current process of criminal case filling at Public Prosecutor's Office to point out some problems. This study suggests a new classification system: at first, each case gets classified based on a case: secondary, the data gets further assorted by the chronological procedures. The classification approach, which is adopted from MoReq 2's Workflow method, is more adjustable to the new electronic filing system.

• Journal of Korean Biological Nursing Science
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• v.18 no.4
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• pp.247-256
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• 2016

Purpose: This study aimed to examine the relationships between the N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels with the sociodemographic and clinical factors, self-care behaviors, and the physical symptom experiences in patients with heart failure. Methods: This cross-sectional study utilized a convenience sample of adult outpatients and inpatients who attended a cardiology department in a tertiary hospital in Seoul, Korea. The data from 154 patients with heart failure were collected using a questionnaire, and their clinical data were extracted from their electronic medical records. Results: Compared with the patients with high NT-proBNP levels, those with low NT-proBNP levels had significantly lower physical symptom experiences scores. Patients with low- and mid-NT-proBNP levels were more likely to be employed compared with those with high NT-proBNP levels. Patients with low NT-proBNP levels had higher left ventricular ejection fractions, and were less likely to have arrhythmias and comorbidities. Conclusion: The results from this study showed that patients with more severe heart failure had higher physical symptom experiences scores; hence, individualizing treatment approaches based on heart failure severity is necessary.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.51-69
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• 2014

Times to multiple events (TMEs) are a major data type in large-scale business and medical data. Despite its importance, the analysis of TME data has not been well studied because of the analysis difficulty from censoring of observation. To address this difficulty, we have developed a Bayesian-based multivariate survival analysis method, which can successfully estimate the joint probability density of survival times. In this work, we extended this method for the analysis of precedence, dependency and causality among multiple events. We applied this method to the electronic health records of 2,111 patients in a children's hospital in the US and the proposed analysis successfully shows the relation between times to two types of hospital visits for different medical issues. The overall result implies the usefulness of the multivariate survival analysis method in large-scale big data in a variety of areas including marketing, human resources, and e-commerce. Lastly, we suggest our future research directions based multivariate survival analysis method.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.137-157
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• 2023

The scale of research and development (R&D) investment is increasing to strengthen national competitiveness through technological innovation, leading to an increased interest in investment efficiency. In records management, the National Archives of Korea has been leading the national research and development project since 2008. Accordingly, this study analyzed R&D projects in records management regarding implementing organization, performance or outcomes, and subjects, targeting 111 National Archives of Korea contract research projects from 2008 to 2022. The analysis showed that small and medium-sized enterprises (SMEs) were the most likely to conduct research, the majority of the research outcomes were academic publications, and there were some discrepancies between the reported performance in research and the actual performance. In terms of research subjects, the most common type of records are paper or print documents, establishing an electronic management system among the National Archives' works. In terms of the frequency of keywords in the records management process and research projects, it was found that research was mainly conducted on "preservation." Meanwhile, only 10 cases, or 9% of the 111 projects, were found to be relevant in terms of utilizing big data and developing intelligent technologies related to digital transformation. Therefore, the effectiveness of the R&D project must be improved through follow-up management of the results even after the research project is completed. In addition, in terms of research topics, it was identified that aside from "preservation," studies focusing on "transfer," "classification," "evaluation," and "collection," as well as research that responds to digital transformation, are needed.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.671-677
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• 2012

A black-box program was implemented in order to monitor abnormal symptoms of human body irregularly occurring during sleep. The system consists of sensor probing body signals, auxiliary devices such as the alarm, lamp, network camera, and signal monitoring computer. Various types of sensors, PPG, ECG, EEG, temperature, respiration sensor, G-sensor, and microphone were used to more exactly identify the causes of abnormal symptoms. If a symptom occurs, the system records the patient's condition to provide information being utilized in the treatment. The sensors are attached on some locations of body being proper to check a specific type of abnormal reaction. Based on the normal range and type of measurement data, criteria of signal levels were set to distinguish abnormal reaction. An abnormal signal being probed, the program starts to operate the lamp, alarm, and network camera at the same time and stores the signal and video data.

• Korean Journal of Biological Psychiatry
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• v.27 no.1
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• pp.18-26
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• 2020

Objectives The aim was to find effective vectorization and classification models to predict a psychiatric diagnosis from text-based medical records. Methods Electronic medical records (n = 494) of present illness were collected retrospectively in inpatient admission notes with three diagnoses of major depressive disorder, type 1 bipolar disorder, and schizophrenia. Data were split into 400 training data and 94 independent validation data. Data were vectorized by two different models such as term frequency-inverse document frequency (TF-IDF) and Doc2vec. Machine learning models for classification including stochastic gradient descent, logistic regression, support vector classification, and deep learning (DL) were applied to predict three psychiatric diagnoses. Five-fold cross-validation was used to find an effective model. Metrics such as accuracy, precision, recall, and F1-score were measured for comparison between the models. Results Five-fold cross-validation in training data showed DL model with Doc2vec was the most effective model to predict the diagnosis (accuracy = 0.87, F1-score = 0.87). However, these metrics have been reduced in independent test data set with final working DL models (accuracy = 0.79, F1-score = 0.79), while the model of logistic regression and support vector machine with Doc2vec showed slightly better performance (accuracy = 0.80, F1-score = 0.80) than the DL models with Doc2vec and others with TF-IDF. Conclusions The current results suggest that the vectorization may have more impact on the performance of classification than the machine learning model. However, data set had a number of limitations including small sample size, imbalance among the category, and its generalizability. With this regard, the need for research with multi-sites and large samples is suggested to improve the machine learning models.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.577-582
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• 2011

EMR(Electronic Medical Record) is an emerging technology that is highly-blended between non-IT and IT area. One of methodology to link non-IT and IT area is to construct databases. Nowadays, it supports before and after-treatment for patients and should satisfy all stakeholders such as practitioners, nurses, researchers, administrators and financial department and so on. In accordance with the database maintenance, DAS (Data as Service) model is one solution for outsourcing. However, there are some scalability and strategy issues when we need to plan to use DAS model properly. We constructed three kinds of databases such as plain-text, MS built-in encryption which is in-house model and custom AES (Advanced Encryption Standard) - DAS model scaling from 5K to 2560K records. To perform custom AES-DAS better, we also devised Bucket Index using Bloom Filter. The simulation showed the response times arithmetically increased in the beginning but after a certain threshold, exponentially increased in the end. In conclusion, if the database model is close to in-house model, then vendor technology is a good way to perform and get query response times in a consistent manner. If the model is DAS model, it is easy to outsource the database, however, some technique like Bucket Index enhances its utilization. To get faster query response times, designing database such as consideration of the field type is also important. This study suggests cloud computing would be a next DAS model to satisfy the scalability and the security issues.