Biomedical term normalization of EHRs with UMLS

by   Naiara Perez, et al.

This paper presents a novel prototype for biomedical term normalization of electronic health record excerpts with the Unified Medical Language System (UMLS) Metathesaurus. Despite being multilingual and cross-lingual by design, we first focus on processing clinical text in Spanish because there is no existing tool for this language and for this specific purpose. The tool is based on Apache Lucene to index the Metathesaurus and generate mapping candidates from input text. It uses the IXA pipeline for basic language processing and resolves ambiguities with the UKB toolkit. It has been evaluated by measuring its agreement with MetaMap in two English-Spanish parallel corpora. In addition, we present a web-based interface for the tool.


Cross-lingual Candidate Search for Biomedical Concept Normalization

Biomedical concept normalization links concept mentions in texts to a se...

CODER: Knowledge infused cross-lingual medical term embedding for term normalization

We propose a novel medical term embedding method named CODER, which stan...

Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization

Cross-lingual word embeddings (CLWE) underlie many multilingual natural ...

MultiAzterTest: a Multilingual Analyzer on Multiple Levels of Language for Readability Assessment

Readability assessment is the task of determining how difficult or easy ...

BVS Corpus: A Multilingual Parallel Corpus of Biomedical Scientific Texts

The BVS database (Health Virtual Library) is a centralized source of bio...

Cross-lingual Argument Mining in the Medical Domain

Nowadays the medical domain is receiving more and more attention in appl...

A language score based output selection method for multilingual speech recognition

The quality of a multilingual speech recognition system can be improved ...

Code Repositories


Búsqueda de evidencia clínica en literatura científica

view repo

Please sign up or login with your details

Forgot password? Click here to reset