Papers Medical Concept Normalization
“Medical Concept Normalization” 태그가 달린 논문 13편 · 필터 해제
Medical Concept Normalization in a Low-Resource Setting
In the field of biomedical natural language processing, medical concept normalization is a crucial task for accurately mapping mentions of concepts to a large knowledge base. However, this task becomes even more challeng…
Medical Concept Normalizationpreon: Fast and accurate entity normalization for drug names and cancer types in precision oncology
Motivation In precision oncology (PO), clinicians aim to find the best treatment for any patient based on their molecular characterization. A major bottleneck is the manual annotation and evaluation of individual varian…
Data IntegrationMedical Concept NormalizationTerm ExtractionCBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice. With the development of biomedical language understanding benchmarks, AI applicat…
Intent ClassificationMedical Concept NormalizationMedical Relation ExtractionNamed Entity Recognition+6C-Norm: a neural approach to few-shot entity normalization
Entity normalization is an important information extraction task which has gained renewed attention in the last decade, particularly in the biomedical and life science domains. In these domains, and more generally in all…
Few-Shot LearningMedical Concept NormalizationSocial Media Medical Concept Normalization using RoBERTa in Ontology Enriched Text Similarity Framework
Pattisapu et al. (2020) formulate medical concept normalization (MCN) as text similarity problem and propose a model based on RoBERTa and graph embedding based target concept vectors. However, graph embedding techniques …
AttributeGraph EmbeddingMedical Concept Normalizationtext similarityTarget Concept Guided Medical Concept Normalization in Noisy User-Generated Texts
Medical concept normalization (MCN) i.e., mapping of colloquial medical phrases to standard concepts is an essential step in analysis of medical social media text. The main drawback in existing state-of-the-art approach …
Medical Concept NormalizationSentenceSentence EmbeddingSentence-EmbeddingMedical Concept Normalization in User-Generated Texts by Learning Target Concept Embeddings
Medical concept normalization helps in discovering standard concepts in free-form text i.e., maps health-related mentions to standard concepts in a clinical knowledge base. It is much beyond simple string matching and re…
Clinical KnowledgeMedical Concept Normalizationtext-classificationText Classification+1Medical Concept Normalization in User Generated Texts by Learning Target Concept Embeddings
Medical concept normalization helps in discovering standard concepts in free-form text i.e., maps health-related mentions to standard concepts in a vocabulary. It is much beyond simple string matching and requires a deep…
General ClassificationMedical Concept Normalizationtext-classificationText Classification+1An ensemble CNN method for biomedical entity normalization
Different representations of the same concept could often be seen in scientific reports and publications. Entity normalization (or entity linking) is the task to match the different representations to their standard conc…
Entity LinkingMedical Concept NormalizationBOUN-ISIK Participation: An Unsupervised Approach for the Named Entity Normalization and Relation Extraction of Bacteria Biotopes
This paper presents our participation to the Bacteria Biotope Task of the BioNLP Shared Task 2019. Our participation includes two systems for the two subtasks of the Bacteria Biotope Task: the normalization of entities (…
Medical Concept NormalizationRelation ExtractionRe-RankingWord EmbeddingsIntegration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature
In this paper, we present our participation in the Bacteria Biotope (BB) task at BioNLP-OST 2019. Our system utilizes fine-tuned language representation models and machine learning approaches based on word embedding and …
BIG-bench Machine LearningMedical Concept NormalizationRelationRelation ExtractionDeep Neural Models for Medical Concept Normalization in User-Generated Texts
In this work, we consider the medical concept normalization problem, i.e., the problem of mapping a health-related entity mention in a free-form text to a concept in a controlled vocabulary, usually to the standard thesa…
FormMedical Concept NormalizationSequence Learning with RNNs for Medical Concept Normalization in User-Generated Texts
In this work, we consider the medical concept normalization problem, i.e., the problem of mapping a disease mention in free-form text to a concept in a controlled vocabulary, usually to the standard thesaurus in the Unif…
Medical Concept NormalizationSemantic SimilaritySemantic Textual Similarity