• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Journal of dental hygiene science
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• v.17 no.6
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• pp.523-532
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• 2017

The purpose of this study was to provide basic data to standardize the clinical dental hygiene curriculum, based on analysis of current clinical dental hygiene curricula in Korea. We emailed questionnaires to 12 schools to investigate clinical dental hygiene curricula, from February to March, 2017. We analyzed the clinical dental hygiene curricula in 5 schools with a 3-year program and in 7 schools with a 4-year program. The questionnaire comprised nine items on topics relating to clinical dental hygiene, and four items relating to the dental hygiene process and oral prophylaxis. The questionnaire included details regarding the subject name, the grade/semester/credit system, course content and class hours, the number of senior professors, and the number of patients available for dental hygiene clinical training purposes. In total, there were 96 topics listed in the curricula relating to clinical dental hygiene training, and topics varied between the schools. There was an average of 20.4 topic credits, and more credits and hours were allocated to the 4-year program than to the 3-year program. On average, the ratio of students to professors was 21.4:1. Course content included infection control, concepts for dental hygiene processes, dental hygiene assessment, intervention and evaluation, case studies, and periodontal instrumentation. An average of 2 hours per patient was spent on dental hygiene practice, with an average of 1.9 visits. On average, student clinical training involved 19 patients and 26.6 patients in the 3-year and 4-year programs, respectively. The average participation time per student per topic was 38.0 hours and 53.1 hours, in the 3-year and 4-year programs, respectively. Standardizing the clinical dental hygiene curricula in Korea will require consensus guidelines on topics, the number of classes required to achieve core competencies as a dental hygienist, and theory and practice time.