• Biomedical Science Letters
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• v.10 no.4
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• pp.485-493
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• 2004

In the current field of Medical Informatics, the information increases, and changes fast, so we can access the various data types which are ranged from text to image type. A small number of technician digitizes these data to establish database, but it is needed a lot of money and time. Therefore digitization by many end-users confronting data and establishment of searching database is needed to manage increasing information effectively. New data and information are taken fast to provide the quality of care, diagnosis which is the basic work in the medicine. And also It is needed the medical database for purpose of private study and novice education, which is tool to make various data become knowledge. However, current medical database is used and developed only for the purpose of hospital work management. In this study, using text input, file import and object images are digitized to establish database by people who are worked at the medicine field but can not expertise to program. Data are hierarchically constructed and then knowledge is established using a tree type database establishment method. Consequently, we can get data fast and exactly through search, apply it to study as subject-oriented classification, apply it to diagnosis as time-depended reflection of data, and apply it to education and precaution through function of publishing questions and reusability of data.

• The Journal of Industrial Distribution & Business
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• v.13 no.11
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• pp.1-10
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• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.345-352
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• 2022

Conducting AI-based fusion business due to the increment of ICT fusion medical device has been expanded. In addition, AI-based medical devices help change existing medical system on treatment into the paradigm of customized treatment such as preliminary diagnosis and prevention. It will be generally promoted to the change of medical device industry. Although the current demand forecasting of medical biotechnology commercialization is based on the method of Delphi and AHP, there is a problem that it is difficult to have a generalization due to fluctuation results according to a pool of participants. Therefore, the purpose of the paper is to predict demand forecasting for identifying promising technology based on building up big data in medical biotechnology. The development method is to employ candidate technologies of keywords extracted from SCOPUS and to use word2vec for drawing analysis indicator, technological distance similarity, and recommended technological similarity of top-level items in order to achieve a reasonable result. In addition, the method builds up academic big data for 5 years (2016-2020) in order to commercialize technology excavation on demand perspective. Lastly, the paper employs global data studies in order to develop domestic and international demand for technology excavation in the medical biotechnology field.

• Journal of Digital Contents Society
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• v.4 no.1
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• pp.57-66
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• 2003

This paper presents the content regarding electronic medical examination chart and data treatment for efficient medical examination and prompt treatment by realizing mutual conversation type remote medical examination system among 3 parties(patient, doctor, pharmacist) on internet base. This is an intelligence type remote medical examination system for both on-line and off-line mode to transcend time and space on the web being participated by anybody, which is cheap type to solve problems in existing remote medical examination system such as high price based on hardware, incompatibility, and so on. By interconnecting ASP and SQL on IIS 4.0 web server, database enables system integration for efficient data processing, on-line consultation between patient and doctor, medical examination on off-line, transmission of medical prescription to pharmacist designated by patient and preparation of medicine, semi-eternal storage of medical examination data owing to storage and search of medical examination data, exact medical examination and prescription using this medical examination data by patient and doctor, and so on.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.39-54
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• 2012

Picture Archiving and Communication System (PACS) has been planted as one of the key infrastructures with an overall improvement in standards of medical informationization and the stream of digital hospitalization in recent days. The kind and data of digital medical imagery are also increasing rapidly in volume. This trend emphasizes the medical image compression for storing large-scale medical image data. Digital Imaging and Communications in Medicine (DICOM), de facto standard in digital medical imagery, specifies Run Length Encode (RLE), which is the typical lossless data compressing technique, for the medical image compression. However, the RLE is not appropriate approach for medical image data with bilateral symmetry of the human organism. we suggest two preprocessing algorithms that detect interested area, the minimum bounding rectangle, in a medical image to enhance data compression efficiency and that re-code image pixel values to reduce data size according to the symmetry characteristics in the interested area, and also presents an improved image compression technique for brain CT imagery with high bilateral symmetry. As the result of experiment, the suggested approach shows higher data compression ratio than the RLE compression in the DICOM standard without detecting interested area in images.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.397-407
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• 2014

Due to rapid development of medical information, a huge amount of information is being accumulated. Desires to conduct clinical researches by using this information are increasing, and medical institutions are encountering problems of aging society and drastic increase of medical expenses. Utilization of Big Data as an alternative is now being emphasized. The purpose of this study is to examine informatization of medical institutions and suggest political implications for Big Data utilization plans. Data was collected through literature searches and interviews with medical information professionals of medical institutions, from September to November, 2013, for four months. As a result of the study, it could be found that the hospital information system is improving from patient management and administration to researches and information strategies. Thus, national supports for medical expense reduction as well as fostering professional manpower should be provided, considering establishment of the system for utilization of Big Data and efficient application of unstructured data.

• Journal of Biomedical Engineering Research
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• v.26 no.5
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• pp.301-307
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• 2005

We introduce a new multimedia telemedicine system which is called Telemedicine for Real-time Emergency Multi-consultation(TREM), based on multiple connection between medical specialists. Due to the subdivision of medical specialties, the existing one-to-one telemedicine system needs be modified to a simultaneous multi-consulting system. To facilitate the consultation the designed system includes following modules: high-quality video, video conferenceing, bio-signal transmission, and file transmission. In order to enhance the operability of the system in different network environment, we made it possible for the user to choose appropriate data acquisition sources of multimedia data and video resolutions. We have tested this system set up in three different places: emergency room, radiologist's office, and surgeon's office. All three communicating systems were successful in making connections with the multi-consultation center to exchange data simultaneously in real-time.

• Genomics & Informatics
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• v.11 no.4
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• pp.186-190
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• 2013

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.225-239
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• 2020

Analysis approaches for single compositional data are well established; however, effective analysis strategies for paired compositional data remain to be investigated. The current project was motivated by studies of age-related hearing loss (presbyacusis), where subjects are classified into four audiometric phenotypes that need to be ranked within these phenotypes based on their paired compositional data. We address this challenge by formulating this problem as a classification problem and integrating a penalized multinomial logistic regression model with compositional data analysis approaches. We utilize Elastic Net for a penalty function, while considering average, absolute difference, and perturbation operators for compositional data. We applied the proposed approach to the presbyacusis study of 532 subjects with probabilities that each ear of a subject belongs to each of four presbyacusis subtypes. We further investigated the ranking of presbyacusis subjects using the proposed approach based on previous literature. The data analysis results indicate that the proposed approach is effective for ranking subjects based on paired compositional data.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.1-6
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• 2019

In this article, we have presented a framework, designed to create new services for businesses, which use large sets of medical data. It is not a simple data analysis step, but it clarifies the purpose of data utilization, analyses it, extracts value from it, and designs a process from actual business or service to an operation. The designed frame work covers the basic architecture and social system model. It was designed, using basic data, which was focused on large sets of medical data, and to be applied to a social system with reference to the designed framework. We are looking forward to create various medical business alliances and services applying the designed framework to the available sets of basic medical data.