지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.1
- 수록면
- 151 - 157 (7page)
이용수
초록· 키워드
오류제보하기
Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).
목차
등록된 정보가 없습니다.
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Strategies to Isolate Drug-resistant Strains and to Identify New Drug Resistance Mechanisms
한국미생물학회 학술대회논문집
2022 .10
-
Quality management strategies for drug development
한국분석과학회 학술대회
2016 .11
-
Erratum to “Analysis of potential drug-drug interactions in the intensive care unit using healthcare claims database and drug information database”
한국데이터정보과학회지
2019 .01
-
Simultaneous analysis and monitoring of preservatives in drugs and quasi drugs
한국분석과학회 학술대회
2016 .05
-
Advancements in Antiviral Drug Development: Comprehensive Insights into Design Strategies and Mechanisms Targeting Key Viral Proteins
Journal of Microbiology and Biotechnology
2024 .07
-
Exploration of Availability as a Signal Indicator about Youden Index
Journal of The Korean Data Analysis Society
2021 .01
-
Development of Analysis Method for New Drug Substance by HPLC
한국분석과학회 학술대회
2023 .11
-
건강보험청구자료와 의약품정보데이터베이스를 이용한 중환자실 약물상호작용 분석
한국데이터정보과학회지
2018 .11
-
OryzaGP: rice gene and protein dataset for named-entity recognition
Genomics & informatics
2019 .01
-
A study on establishment of standard spectrum for chemical drug in korea pharmacopoeia
한국분석과학회 학술대회
2017 .05
-
외국인 마약사범 증가에 따른 국내 마약정책 개선방안
한국재난정보학회 논문집
2022 .12
-
Utilization of LC-MS/MS in Drug Development
한국분석과학회 학술대회
2024 .11
-
딥 러닝과 KSTAR 초전도 자석
물리학과 첨단기술
2022 .04
-
Drug metabolite identification using MS-based molecular networking
한국분석과학회 학술대회
2021 .11
-
Screening druggable targets and predicting therapeutic drugs for COVID-19 via integrated bioinformatics analysis
Genes & Genomics
2021 .01
-
Single-molecule FRET–based approach for protein-targeted drug discovery
Molecules and Cells
2024 .01
-
Monitoring of anti-impotence drug, anti-obesity drugs and their analogues in foods
한국분석과학회 학술대회
2016 .05
-
Gold Nanoparticles Conjugation Enhances Antiacanthamoebic Properties of Nystatin, Fluconazole and Amphotericin B
Journal of Microbiology and Biotechnology
2019 .01
-
Targeted strategy for rapid and simultaneous measurement of antiepileptic drugs in human serum by liquid chromatography-tandem mass spectrometry as tool for clinical therapeutic drug monitoring
한국분석과학회 학술대회
2022 .11
-
신종 마약류 증가에 따른 대응방안
한국재난정보학회 논문집
2023 .06
이 논문의 저자 정보
최근 본 자료
댓글(0)
0