• 제목/요약/키워드: Medical text

검색결과 698건 처리시간 0.03초

본초 및 용량 용어를 이용한 방제구성 자동추출방법에 대한 연구 -『의종손익』을 중심으로- (A Research on Automatic Data Extract Method for Herbal Formula Combinations Using Herb and Dosage Terminology - Based on 『Euijongsonik』 -)

  • 금유정;이병욱;엄동명;송지청
    • 대한한의학원전학회지
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    • 제33권4호
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    • pp.67-81
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    • 2020

  • Objectives : This research aims to suggest a automatic data extract method for herbal formula combinations from medical classics' texts. Methods : This research was carried out by using Access of Microsoft Office 365 in Windows 10 of Microsoft. The subject text for extraction was 『Euijongsonik』. Using data sets of herb and dosage terminology, herbal medicinals and their dosages were extracted. Afterwards, using the position value of the character string, the formula combinations were automatically extracted. Results :The PC environment of this research was Intel Core i7-1065G7 CPU 1.30GHz, with 8GB of RAM and a Windows 10 64bit operation system. Out of 6,115 verses, 19,277 herb-dosage combinations were extracted. Conclusions : In this research, it was demonstrated that in the case of classical texts that are available as data, knowledge on herbal medicine could be extracted without human or material resources. This suggests an applicability of classical text knowledge to clinical practice.

  • https://doi.org/10.14369/jkmc.2020.33.4.067 인용 PDF KSCI

판본별 교감을 통한 『동의보감』의 정본화 (A Comparative Analysis about Various Editions of Donguibogam)

  • 이정현;오준호
    • 한국의사학회지
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    • 제31권1호
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    • pp.57-70
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    • 2018

  • Much research has already been done on Donguibogam. However, comparison of specific characters was not done because researchers found it difficult to compare different editions of the text in one place. Recently, important editions have been published on the Internet, making comparison possible. In this paper, researchers compare eight editions Donguibogam, including the original edition published in 1613 and seven other editions corrected by the Naeuiwon (Joseon Dynasty National Medical Center). The comparison results were summarized and tabulated. The results of the comparison are analyzed and presented in this article as a chart. The result of comparing the characters and the analyzed graph were in agreement. The authors propose that all written and electronic publications of Donguibogam should refer to other editions implied, quoted or referenced within the text and including with proper citations, and reference the original and first edition. Inadequate referencing will pollute future knowledge of this foundational text of Traditional Korean Medicine and may result in perpetration of mis-information. Based on accumulated knowledge and study of historical Korean Medicine texts, the Namsan edition made a mistake in the editing process. The year of publication of Gabsul-yoengyoeng-gegan Edition needs to be studied again and corrections made where appropriate.

  • https://doi.org/10.15521/jkmh.2018.31.1.057 인용 PDF

고문헌 지식활용을 위한 DB구조에 관한 고찰 (A Study on the Database Structure for Utilizing Classical Literature Knowledge)

  • 우동현;김기욱;이병욱
    • 한국의사학회지
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    • 제33권2호
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    • pp.89-104
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    • 2020

  • The purpose of this research is to build a database structure that can be useful for evidence-based medical practices by constructing the knowledge related to oriental medicine in the classical literature knowledge in a form that can utilize new forms of information technology. As a method, "database" is used as a keyword to search published studies in the field of oriental medicine, research is conducted on classic literature knowledge, and studies describing the contents of the data structure are found and analyzed. In conclusion, the original text DB for the preservation of the original texts and the presentation of the supporting texts should include 'Contents Text', 'Tree Structure', 'Herbal Structure', 'Medicine Manufacture', and 'Disease Structure' tables. In order to search, calculate, and automatically extract expressions written in the original text of the old literature, the tool DB should include 'Unit List', 'Capacity Notation List', 'CUI', 'LUI', and 'SUI' tables. In addition, In order to manage integrated knowledge such as herbal, medicine, acupuncture, disease, and literature, and to implement a search function such as comparison of similarity of control composition, the knowledge DB must contain 'dose-controlled medicine name', 'dose-controlled medicine composition', 'relational knowledge', 'knowledge structure', and 'computational knowledge' tables.

  • https://doi.org/10.15521/jkmh.2020.33.2.089 인용 PDF KSCI

합성 텍스트 생성을 위한 ChatGPT 기반 의료 텍스트 증강 도구 개발 (Development of ChatGPT-based Medical Text Augmentation Tool for Synthetic Text Generation)

  • 공진우;김기연;김유섭;오병두
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
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    • pp.3-4
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    • 2023

  • 자연어처리는 수많은 정보가 수집된 전자의무기록의 비정형 데이터에서 유의미한 정보나 패턴 등을 추출해 의료진의 의사결정을 지원하고, 환자에게 더 나은 진단이나 치료 등을 지원할 수 있어 큰 잠재력을 가지고 있다. 그러나 전자의무기록은 개인정보와 같은 민감한 정보가 다수 포함되어 있어 접근하기 어렵고, 이로 인해 충분한 양의 데이터를 확보하기 어렵다. 따라서 본 논문에서는 신뢰할 수 있는 의료 합성 텍스트를 생성하기 위해 ChatGPT 기반 의료 텍스트 증강 도구를 개발하였다. 이는 사용자가 입력한 실제 의료 텍스트로 의료 합성 데이터를 생성한다. 이를 위해, 적합한 프롬프트와 의료 텍스트에 대한 전처리 방법을 탐색하였다. ChatGPT 기반 의료 텍스트 증강 도구는 입력 텍스트의 핵심 키워드를 잘 유지하였고, 사실에 기반한 의료 합성 텍스트를 생성할 수 있다는 것을 확인할 수 있었다.

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