• 정보관리연구
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• 제32권2호
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• pp.26-39
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• 2001

효과적인 정보검색 도구로 활용되는 시소러스, 분류표 등의 통제어휘집들은 동일한 개념이나 의미를 표현하는데 서로 다른 어휘를 사용하고 있다. 이러한 동일 개념에 대한 용어 표현차이로 인한 정보의 검색 및 통합문제를 해결하기 위하여 미국국립의학도서관은 통합의학언어시스템(Unified Medical Language System : 이하 UMLS)을 개발하였다. UMLS 개발은 1986년부터 시작된 장기 프로젝트로서 2001년판 UMLS는 메타시소러스, 의미망, 전문가 사전의 세가지 요소로 구성되어 있다. 본고는 UMLS의 개발배경과 구성요소 및 PubMed, NLM Gateway에서의 적용사례에 대해 고찰하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.129-132
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• 2003

The metathesaurus(UMLS, 2003AA edition) supports multi language and includes 875, 233 concepts, 2, 146, 897 concept names. It is impossible for PubMed or NLM serve searching of the metatheaurus to retrieval using a query that is not to be text, a fault sentence structure or a part of concept name. That means the user notice correctly suitable medical words in order to get correct answer, otherwise she or he can't find information that they want to find I propose that the method of searching unified medical language system using automatic modified a query for problem that I mentioned. This method use dictionary that is standard for automation of modified query gauge similarity between query and dictionary using string comparison algorithm. And then, the tested term converse the form of metathesaurus for optimized result. For the evaluation of method, I select some query and I contrast NLM method that renewed Aug. 2003.

• 대한한의정보학회지
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• 제16권1호
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• pp.1-8
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• 2010

Objective: Various controlled vocabulary such as thesaurus and classification make us to reuse and share effectively by defining different concept and linking terms each other. The UMLS(Unified Medical Language System) is one of the most universal medical terminology systems. It is needed various methods to share and reuse information of traditional Korean medicine. We will research on method that adopt SUI of the UMLS(that is de facto standard in medical terminology system) in traditional Korean medical terminology. Method: We described major problems and applying process when we tried to add traditional Korean medicine in the part of meridian into the UMLS metathesaurus. Comparing western medical terms and traditional Korean medical terms for applying UMLS metathesaurus, there is not only many consistency, but also differences. Result: We confirmed what is the differences and consistency between western medical terms and traditional Korean medical terms. And then reviewed methods that apply the CUI, LUI, SUI in traditional Korean medical terms. Traditional Korean medical terms are not discriminated by singular or plural string. In addition, traditional Korean medical terms have vary string by initial law: the law of initial sound of a syllable. Character is described with Korean, traditional Chinese, modern Chinese, etc. According to meaning, language, initial law, SUI has a distinct value respectively. Conclusion: There are many differences to apply the UMLS between western medical terms and traditional Korean medical terms. For the better implementation to traditional Korean medicine into the UMLS, further research is needed in standardization and classification of traditional Korean medical terms, medical information system, etc. We hope this study helps the implementation UMLS, EHR, knowledge based system in Oriental medicine in the future.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.50-52
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• 2009

Ontology maintenance is a time consuming and costly process which requires special skill and knowledge. It requires joint effort of both ontology engineer and domain specialist to properly maintain ontology and update knowledge in it. This is specially true for medical domain which is highly specialized domain. This paper proposes a novel approach for maintenance and update of existing ontologies in a medical domain. The proposed approach is based on modified Ontology Maturing Process which was originally developed for web domain. The proposed approach provides way to populate medical ontology with new knowledge obtained from medical documents. This is achieved through use of natural language processing techniques and highly specialized medical knowledge bases such as Unified Medical Language System.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제11권1호
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• pp.35-40
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• 2022

본 논문에서는 임상 의사 결정 지원을 위하여 의학 지식을 통해 임상 관계를 추출하고 딥러닝 모델을 이용하여 질병을 예측하는 방법을 제안한다. 의학 사전인 UMLS(Unified Medical Language System)와 암 관련 의학 지식에 포함된 임상 용어를 5가지로 분류한다. 분류된 임상 용어들을 사용하여 위키피디아 의학 문서를 추출한다. 추출한 위키피디아 의학 문서와 추출한 임상 용어를 매칭하여 임상 관계를 구축한다. 구축한 임상 관계를 이용하여 딥러닝 학습을 진행한 후 질의에서 표현된 의학 용어를 바탕으로 질의와 연관된 질병을 예측한다. 이후, 예측한 질병과 관계가 있는 의학 용어를 확장 질의로 선택한 뒤 질의를 확장한다. 제안 방법의 유효성을 검증하기 위해 TREC Clinical Decision Support(CDS), TREC Precision Medicine(PM) 테스트 컬렉션에 대해 비교 평가한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.270-272
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• 2022

임상을 거친 약물이 시중에 유통되지 못하는 요인 중 하나는 안전성이다. 약물 부작용으로 인해 발생하는 안전성 문제의 주된 원인인 신경독성의 경우, 사전에 약물이나 화합물에 대한 위험 평가가 필요하다. 현재 약물의 안전성 검사를 위한 실험들은 동물 실험을 기반으로 하고 있으며, 이는 시간과 비용이 많이 든다는 단점을 갖는다. 따라서 위 문제를 해결하기 위해 in silico 실험을 통한 신경독성 예측모델을 제안하고자 한다. 본 연구에서는 의학 언어 시스템 (Unified Medical Language System)을 이용해 신경독성의 범주를 확대하고, 통합 데이터베이스를 기반으로 다양한 관련 화합물 데이터를 얻었다. 얻은 화합물들의 SMILES (Simplified Molecular Input Line Entry System)를 fingerprint로 변환시키고 이를 사용한 기계학습 기반의 모델을 만들었다. 모델은 최종적으로 신경독성의 유무를 예측한다. 해당 연구에서 제안된 실험은 in vivo 실험에 소요되는 시간 및 비용을 줄일 수 있다. 더 나아가 신약 개발 연구 기간을 단축하고 개발 중지 등의 부담을 줄일 수 있을 것으로 기대된다.

• 대한한의학원전학회지
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• 제23권6호
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• pp.15-26
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• 2010

Objective This is a previous study for including traditional Korean medical terms into the UMLS(The Unified Medical Language System) and achieving the interoperability between various medical systems. Method First, the traditional medical terms were divided into 4 categories : basic theory, acupuncture, herb and formulae. And then, searching these terms through metathesaurus in UMLSKS(UMLS Knowledge Source Server), terminology information was investigated and analyzed. Results In the case of TM title, traditional Korean medicine was categorized as different semantic type from Traditional medicine, Traditional Chinese medicine and Kampo medicine. Acupuncture points were described only as abbreviation and herbs were conceptualized inconsistently, as some belonged to scientific name and some belonged to Chinese pronunciation. Formulaes are described as Chinese, Japanese and Korean pronunciations. Conclusions More research is needed on diagnosis/disease terms and semantic types for the unique concepts in traditional Korean medicine in order to including the international standard.

• 대한한의학원전학회지
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• 제22권1호
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• pp.191-205
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• 2009

Objective : Up to the present, theories of medical books is too difficult to understand thoroughly. However, these study methods have some problems in dealing with lots of meaning because the comprehension of theories are dependent upon one's memory. Especially, comparison distinct medical books are more difficult matter. So, we have attempted to solve a problem. Method : We have researched medical terms in the "Piweilun" according to below the procedure. (1) Making a terms list: We have selected constituent of sentence. And we have made term list on the basis of concept of term. (2) Making a synonym list: We have collected identical conception and made a synonym list. So, using an synonym tables of DB, it is possible to search for the non-standard terms of medical theory. (3) Making a classification system: Using UMLS(Unified Medical Language System), MeSH(Medical Subject Headings), IST(International Standard Terminology) ect., we have made a classification system of oriental medicine terms in the "Piwelun". Analysis of relation between terms. Result : In the "Piweilun", there are more than 1,790s concepts. Parts of those are belonged to UMLS-Semantic Type, the other parts of those are not belonged to UMLS-Semantic Type. And those include predicate more than UMLS-Semantic Relations.

• 대한한의학원전학회지
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• 제23권1호
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• pp.59-79
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• 2010

Objective : We did a comparative study about characteristics of oriental medical books. As a result, we took notice of classification in the nominal terms by semantic type of UMLS(Unified Medical Language System). By using classified nominal terms, comparative study can be more effectively. So, we selected another oriental medical book and classified nominal terms in it by semantic type of UMLS. By result of classification, we have attempted to study about comparison between oriental medical books and development of medical theories. Method :We have made a comparative study on classification in the nominal terms between "Biwiron(脾胃論)" and "Soayakjeungjikgyeol(小兒藥證直訣)" according to the below the procedure. (1) Making a nominal terms list of "Soayakjeungjikgyeol(小兒藥證直訣)" and grasping contextual meaning of nominal terms of it. (2) Modification and supplementation about semantic type of UMLS for "Soayakjeungjikgyeol(小兒藥證直訣)". Using the modified classification system, we classified nominal terms. After this process, we arranged classified nominal terms by Haansoft Hangul 2007. (3) Comparing classified nominal terms between "Biwiron(脾胃論)" and "Soayakjeungjikgyeol(小兒藥證直訣)". Result : In the "Soayakjeungjikgyeol(小兒藥證直訣)", there are more than 2,519's nominal terms and different categories of semantic type of UMLS classification from "Biwiron(脾胃論)". Through comparison between their classification of nominal terms, we can understand the characteristics of the two and their development of medical theories.

• Journal of Information Science Theory and Practice
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• 제3권1호
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• pp.6-23
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• 2015

This study develops an effective method for sentiment analysis of user-generated content on drug review websites, which has not been investigated extensively compared to other general domains, such as product reviews. A clause-level sentiment analysis algorithm is developed since each sentence can contain multiple clauses discussing multiple aspects of a drug. The method adopts a pure linguistic approach of computing the sentiment orientation (positive, negative, or neutral) of a clause from the prior sentiment scores assigned to words, taking into consideration the grammatical relations and semantic annotation (such as disorder terms) of words in the clause. Experiment results with 2,700 clauses show the effectiveness of the proposed approach, and it performed significantly better than the baseline approaches using a machine learning approach. Various challenging issues were identified and discussed through error analysis. The application of the proposed sentiment analysis approach will be useful not only for patients, but also for drug makers and clinicians to obtain valuable summaries of public opinion. Since sentiment analysis is domain specific, domain knowledge in drug reviews is incorporated into the sentiment analysis algorithm to provide more accurate analysis. In particular, MetaMap is used to map various health and medical terms (such as disease and drug names) to semantic types in the Unified Medical Language System (UMLS) Semantic Network.