• 대한한의학원전학회지
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• 제36권1호
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• pp.33-43
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• 2023

Objectives : Overlapping contents between two recently discovered Han period bamboo slats, the so-called "Beidahanjian" and the "Liushibingfang" have been identified. This study aims to present new knowledge that could be inferred from the concordance of these two texts. Methods : The most recent original texts of the medical part of the Beidahanjian and medical texts excavated from the Laoguanshan in addition to the Liushibingfang were compared with each other to determine identical parts. The meaning of these concordances was explored. Results : Identical sentences in two verses in the Beidahanjian and the Laoguanshan were identified. Conclusions : The Beidahanjian is a credible Western Han period text, of which the medical bamboo slats are likely to comprise an independent text that is a combination of ancient folk prescriptions and those of doctors.

• 한국응급구조학회지
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• 제24권1호
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• pp.85-92
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• 2020

Purpose: The purpose of this study was to analyze the English abstract key words found within the Korea Society of Emergency Medical Services journal using text mining techniques to determine the adherence of these terms with Medical Subject Headings (MeSH) and identify key word trends. Methods: We analyzed 212 papers that were published from 2012 to 2019. R software, web scraping, and frequency analysis of key words were conducted using R's basic and text mining packages. Additionally, the Word Clouds package was used for visualization. Results: The average number of key words used per study was 3.9. Word cloud visualization revealed that CPR was most prominent in the first half and emergency medical technician was most frequently used during the second half. There were a total of 542 (64.9%) words that exactly matched the MeSH listed words. A total of 293 (35%) key words did not match MeSH listed words. Conclusion: Researchers should obey submission rules. Further, journals should update their respective submission rules. MeSH key words that are frequently cited should be suggested for use.

• 의학교육논단
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• 제19권3호
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• 대한의용생체공학회:의공학회지
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• 제36권3호
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• pp.55-60
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• 2015

An effective image retrieval system is required as the amount of medical imaging data is increasing recently. Authors reviewed the recent development of text-based medical image retrieval including the use of controlled vocabularies - RadLex (Radiology Lexicon), FMA (Foundational Model of Anatomy), etc - natural language processing, semantic ontology, and image annotation and markup.

• 한국의사학회지
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• 제32권1호
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• pp.1-10
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• 2019

The Taesangugeupbang (Emergency Prescriptions for Childbirth) is a medical text written by Li-Chengong of China in the early 14th century. It incorporates forms of obstetrics and gynecology in use in the Chosun Dynasty and is quoted in the Hyangyakjibsungbang (Compendium of Prescription from the Countryside), the Euibangyoochui (Classified Collection of Medical Prescriptions), and the Taesanjibyo (Collection of Essentials for Childbirth). The recent rediscovery of Taesangugeupbang manuscripts in Japan has enabled full-scale research of this text. This article is based on a study of these manuscripts and attempts to synthesize the text through the various documents. The article suggests that: (1) critical texts for understanding the Taesangugeupbang include the Uijeoggo (A Review of Medical Books), the Euibangyoochui, and the Taesanjibyo; (2) there is a possibility that the Taesangugeupbang had disappeared from use in Joseon by the late 15th century; (3) the Taesangugeupbang complemented the treatment regimen of other texts and influenced the development of early Chosun ophthalmology; (4) The Taesangugeupbang is quoted in many Joseon's medical texts and is related to the author's mentor.

• 대한한의학원전학회지
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• 제34권2호
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• pp.63-74
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• 2021

Objectives :This paper analyzes the newly discovered manuscripts of the Sanghanjijangdo(傷寒指掌圖). A bibliographic study was carried out to examine the contents and the background of publication. Methods : First, a bibliographical analysis of the Joseon text was conducted. Next, the contents of the composition were compared with the Yuanand early Ming publications of China. Results : 1. The Joseon publication was published based on the original publication from the Yuan period. The Sanghanjijangdo has been cited in several medical texts from early Joseon such as the Euibangyuchwi and Hyangyakjipseongbang. 3. The background for publication of the Sanghanjijangdo is as following. First, it is an introductory text for beginners of Shanghan[cold damage] studies. Second, its contents do not conflict with the specialized Shanghan text that was used as the textbook for the royal physician examination. Third, it contains many Shanghan formulas that could be composed of domestic drugs only. Conclusions : The Sanghanjijangdo could be described as an introductory text for beginners of Shanghan studies that contributed to the expansion of the base of Shanghan studies in 15c mid-Joseon. Publication of this book clearly shows that Shanghan studies in early Joseon was practiced within the scopes of practicality and localization of medicinals.

• 대한한의학원전학회지
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• 제34권1호
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• pp.1-25
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• 2021

Objectives : The purpose of this paper is to analyze the text of the 『HaeHokByeonUi(解惑辨疑)』 in detail and to collect information on its author, Lee, ByungHa. Methods : Family and life of Lee, ByungHa were reconstructed through genealogy and historical data published by the government. The contents and frequency of title items were analyzed. Results :1. The period of writing is estimated to be between 1827-1831. 2. At that time, there were one JeonUigam(典醫監)-bujigjang(副直長), and four medical officers who belonged to the Chijongcheong(治腫廳). 3. There was a total of 2434 title items, of which 472 items were overlaps. 4. The proportion of general vocabulary is higher than that of other vocabulary. 5. The overlapping title items are presumed to be important basic concepts within the medical text of that time. Conclusions : 『HaeHokByeonUi(解惑辨疑)』 was likely an introductory text to those preparing for the National Medical Examination of the 19th century. It provides useful basic medical vocabulary to learners of Korean Medicine even today.

• 대한한의학원전학회지
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• 제26권1호
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• pp.79-83
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• 2013

Objective : Osim((惡心) stands for nausea which usually precede vomiting(嘔吐). Although it is very common symptom, we can't find the word Osim in some ancient classics. So we tried to find when it had appeared, and what had been its substitute in former medical classics. Material and Methods : The digitalized text in Zhonghuayidian(中華醫典) was used for text search. The text search was performed chronologically. Results : We found that there had been yokto(欲吐), yokgu(欲嘔), geongu(乾嘔), beon(煩), beonsim (煩心), simbeon(心煩), min(悶), ongi(溫氣) as the precedent expression of osim(惡心), which had appeared in Jebyungwonhuron(諸病源候論, 610) for the first time. Conclusion : Until Tang dynasty, there had been kinds of alternative expressions correspond to osim(nausea).

• 한국IT서비스학회지
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• 제18권2호
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• 대한의용생체공학회:의공학회지
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• 제45권4호
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• pp.187-194
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• 2024

In this study, text network analysis was performed using PMS(Post-Marketing Surveillance) data collected from the FDA's MAUDE(Manufacturer and User Facility Device Experience) database to evaluate the usability of the central monitoring system. Based on the data reported from January 1, 2021 to June 30, 2023, keywords related to the central monitoring system were extracted and visualized with a text network. By analyzing the eigenvector centrality of text network, we identified hazards and types of hazardous situations related to usability of the central monitoring system. Eigenvector centrality was chosen because it is relatively more accurate than other centralities. In addition, we derived an appropriate use scenario to evaluate the usability of the central monitoring system. The research results provide more realistic and valuable insights through data derived based on actual adverse event cases, and are expected to contribute to improving safety and reliability by identifying user requirements for improved usability and reducing use errors in the future.