• Title/Summary/Keyword: Medical Big data

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Improving Legislation on the use of Healthcare Data for Research Purposes (보건의료 빅데이터의 연구목적 사용에 대한 법제 개선방안)

  • Park, Dae Woong;Jeong, Hyun Hak;Jeong, Myung Jin;Ryoo, Hwa Shin
    • The Korean Society of Law and Medicine
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    • v.17 no.2
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    • pp.315-346
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    • 2016
  • With the development of big data processing technology, the potential value of healthcare big data has attracted much attention. In order to realize these potential values, various research using the healthcare big data are essential. However, the big data regulatory system centered on the Personal Information Protection Act does not take into account the aspect of big data as an economic material and causes many obstacles to utilize it as a research purpose. The regulatory system of healthcare information, centered on the primary purpose of patient treatment, should be improved in a way that is compatible with the development of technology and easy to use for public interest. To this end, it is necessary to examine the trends of overseas legal system reflecting the concerns about the balance of protection and utilization of personal information. Based on the implications of the overseas legal system, we can derive improvement points in the following directions from our legal system. First, a legal system that specializes in healthcare information and encompasses protection and utilization is needed. De-identification, which is an exception to the Privacy Act, should also clearly define its level. It is necessary to establish a legal basis for linking healthcare big data to create synergy effects in research. It is also necessary to examine the introduction of the opt-out system on the basis of the discussion on the foreign debate and social consensus. But most importantly, it is the people's trust in these systems.

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Construction and Performance Evaluation of Standard System for Medical Big Data (의료 빅데이터를 위한 표준화 시스템 구축 및 성능평가)

  • Kim, Seung-Jin;Jeong, Chang-Won;No, Si-Hyeong;Kim, Ji-Eon;Kim, Tae-Hoon;Jun, Hong Yong;Lee, Yun Oh;Yoon, Kwon-Ha
    • Annual Conference of KIPS
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    • 2018.05a
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    • pp.275-276
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    • 2018
  • 본 논문에서는 원광대학교병원 의료정보시스템의 임상데이터를 OHDSI 가 제안하는 공통데이터 모델로 변환하여 표준화 시스템 구축에 대해서 기술한다. 또한, 검색속도 향상을 위해 인덱싱 기법을 적용한 성능평가 결과를 보인다. 구축된 표준화 시스템은 다양한 임상연구에 활용될 것을 기대하고 있다.

Standardization Trends on Artificial Intelligence in Medicine (의료 인공지능 표준화 동향)

  • Jeon, J.H.;Lee, K.C.
    • Electronics and Telecommunications Trends
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    • v.34 no.5
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    • pp.113-126
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    • 2019
  • Based on the accumulation of medical big data, advances in medical artificial intelligence technology facilitate the timely treatment of disease through the reading the medical images and the increase of prediction speed and accuracy of diagnoses. In addition, these advances are expected to spark significant innovations in reducing medical costs and improving care quality. There are already approximately 40 FDA approved products in the US, and more than 10 products with K-FDA approval in Korea. Medical applications and services based on artificial intelligence are expected to spread rapidly in the future. Furthermore, the evolution of medical artificial intelligence technology is expanding the boundaries or limits of various related issues such as reference standards and specifications, ethical and clinical validation issues, and the harmonization of international regulatory systems.

Diagnosis Analysis of Patient Process Log Data (환자의 프로세스 로그 정보를 이용한 진단 분석)

  • Bae, Joonsoo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.126-134
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    • 2019
  • Nowadays, since there are so many big data available everywhere, those big data can be used to find useful information to improve design and operation by using various analysis methods such as data mining. Especially if we have event log data that has execution history data of an organization such as case_id, event_time, event (activity), performer, etc., then we can apply process mining to discover the main process model in the organization. Once we can find the main process from process mining, we can utilize it to improve current working environment. In this paper we developed a new method to find a final diagnosis of a patient, who needs several procedures (medical test and examination) to diagnose disease of the patient by using process mining approach. Some patients can be diagnosed by only one procedure, but there are certainly some patients who are very difficult to diagnose and need to take several procedures to find exact disease name. We used 2 million procedure log data and there are 397 thousands patients who took 2 and more procedures to find a final disease. These multi-procedure patients are not frequent case, but it is very critical to prevent wrong diagnosis. From those multi-procedure taken patients, 4 procedures were discovered to be a main process model in the hospital. Using this main process model, we can understand the sequence of procedures in the hospital and furthermore the relationship between diagnosis and corresponding procedures.

A Study on the Change of Tourism Marketing Trends through Big Data

  • Se-won Jeon;Gi-Hwan Ryu
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.166-171
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    • 2024
  • Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

Analytic Hierarchy Process for Prioritizing Radiation Safety Measures in Medical Institutions

  • Hyun Suk Kim;Heejeong Jeong;Hyungbin Moon;Sang Hyun Park
    • Journal of Radiation Protection and Research
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    • v.49 no.1
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    • pp.40-49
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    • 2024
  • Background: This study aimed to prioritize policy measures to improve radiation safety management in medical institutions using the analytic hierarchy process. Materials and Methods: It adopted three policy options-engineering, education, and enforcement-to categorize safety management measures, the so-called Harvey's 3Es. Then, the radiation safety management measures obtained from the current system and other studies were organized into action plan categories. Using the derived model, this study surveyed 33 stakeholders of radiation safety management in medical institutions and analyzed the importance of each measure. Results and Discussion: As a result, these stakeholders generally identified enforcement as the most important factor for improving the safety management system. The study also found that radiation safety officers and medical physicists perceived different measures as important, indicating clear differences in opinions among stakeholders, especially in improving quality assurance in radiation therapy. Hence, the process of coordination and consensus is likely to be critical in improving the radiation safety management system. Conclusion: Stakeholders in the medical field consider enforcement as the most critical factor in improving their safety management systems. Specifically, the most crucial among the six specific action plans was the "reinforcement of the organization and workforce for safety management," with a relative importance of 25.7%.

Clinical Study on the Relations of the Thickness and the Stiffness of Back Skin of the Hand to Sasang Constitutions Depending on Sex and Age (연령 및 성별에 따른 사상체질별 손등 피부의 두께와 경도 특성에 대한 임상 연구)

  • Lee, Su-Heon;Choi, Sun-Mi;Kim, Hong-Gie;Kim, Jong-Yeol
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.19 no.2
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    • pp.561-567
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    • 2005
  • We statistically analyzed the relationship between the constitution and the thickness and stiffness of skin depending on sex and age, using 1079 clinical data registered to SCIB(Sasang constitution Information Bank), and the following results are obtained : The thickness of skin has big discrimination ability in classification of Taeeumin and Soyangin, especially in women and in ages 21 or more. The stiffness of skin also has big discrimination ability in classification of Taeeumin and Soeumin, especially in Taeumin women and Soeumin man and in ages 21-60. The differences stated above have been proved to be meaningful enough by Chi-square test.

Clinical Study on the Relations of the Refineness and the Tactile of Back Skin of the Hand to Sasang Constitutions depending on sex and age (연령 및 성별에 따른 사상체질별 손등 피부의 조직 세밀도 및 감촉 특성에 대한 임상 연구)

  • Lee, Su-Heon;Joo, Jong-Cheon;Yoon, Yoo-Sik;Kim, Jong-Yeol
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.19 no.2
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    • pp.536-543
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    • 2005
  • We statistically analyzed the relationship between the constitution and the refineness and tactile of skin depending on sex and age, using 1079 clinical data registered to SCIB(Sasang constitution Information Bank), and the following results are obtained: The thickness of skin has big discrimination ability in classification of Taeeumin and Soyangin, especially in women and in ages 21 or more. The stiffness of skin also has big discrimination ability in classification of Taeeumin and Soeumin, especially in Taeumin women and Soeumin man and in ages 21-60. The differences stated above have been proved to be meaningful enough by Chi-square test.

Association Between Persistent Treatment of Alzheimer's Dementia and Osteoporosis Using a Common Data Model

  • Seonhwa Hwang;Yong Gwon Soung;Seong Uk Kang;Donghan Yu;Haeran Baek;Jae-Won Jang
    • Dementia and Neurocognitive Disorders
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    • v.22 no.4
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    • pp.121-129
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    • 2023
  • Background and Purpose: As it becomes an aging society, interest in senile diseases is increasing. Alzheimer's dementia (AD) and osteoporosis are representative senile diseases. Various studies have reported that AD and osteoporosis share many risk factors that affect each other's incidence. This aimed to determine if active medication treatment of AD could affect the development of osteoporosis. Methods: The Health Insurance Review and Assessment Service provided data consisting of diagnosis, demographics, prescription drug, procedures, medical materials, and healthcare resources. In this study, data of all AD patients in South Korea who were registered under the national health insurance system were obtained. The cohort underwent conversion to an Observational Medical Outcomes Partnership-Common Data Model version 5 format. Results: This study included 11,355 individuals in the good persistent group and an equal number of 11,355 individuals in the poor persistent group from the National Health Claims database for AD drug treatment. In primary analysis, the risk of osteoporosis was significantly higher in the poor persistence group than in the good persistence group (hazard ratio, 1.20 [95% confidence interval, 1.09-1.32]; p<0.001). Conclusions: We found that the good persistence group treated with anti-dementia drugs for AD was associated with a significant lower risk of osteoporosis in this nationwide study. Further studies are needed to clarify the pathophysiological link in patients with two chronic diseases.

Suggestions for the Study of Acupoint Indications in the Era of Artificial Intelligence (인공지능시대의 경혈 주치 연구를 위한 제언)

  • Chae, Youn Byoung
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.35 no.5
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    • pp.132-138
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    • 2021
  • Artificial intelligence technology sheds light on new ways of innovating acupuncture research. As acupoint selection is specific to target diseases, each acupoint is generally believed to have a specific indication. However, the specificity of acupoint selection may be not always same with the specificity of acupoint indication. In this review, we propose that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Using forward inference, the prescribed acupoints for each disease can be quantified for the specificity of acupoint selection. Using reverse inference, targeted diseases for each acupoint can be quantified for the specificity of acupoint indication. It is noteworthy that the selection of an acupoint for a particular disease does not imply the acupoint has specific indications for that disease. Electronic medical record includes various symptoms and chosen acupoint combinations. Data mining approach can be useful to reveal the complex relationships between diseases and acupoints from clinical data. Combining the clinical information and the bodily sensation map, the spatial patterns of acupoint indication can be further estimated. Interoperable medical data should be collected for medical knowledge discovery and clinical decision support system. In the era of artificial intelligence, machine learning can reveal the associations between diseases and prescribed acupoints from large scale clinical data warehouse.