Medical Concept Normalization
4 papers with code • 3 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Medical Concept Normalization
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BB
CHIP-CDN
Latest papers with no code
Medical Concept Normalization in User Generated Texts by Learning Target Concept Embeddings
Second, it finds cosine similarity between embeddings of input concept mention and all the target concepts.
BOUN-ISIK Participation: An Unsupervised Approach for the Named Entity Normalization and Relation Extraction of Bacteria Biotopes
Our participation includes two systems for the two subtasks of the Bacteria Biotope Task: the normalization of entities (BB-norm) and the identification of the relations between the entities given a biomedical text (BB-rel).
Integration 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.
Deep 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 thesaurus in the Unified Medical Language System (UMLS).
Sequence 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 Unified Medical Language System (UMLS).
