A Systematic Approach to Configuring MetaMap for Optimal Performance.

ABSTRACT:

Background

MetaMap is a valuable tool for processing biomedical texts to identify concepts. Although MetaMap is highly configurative, configuration decisions are not straightforward.

Objective

To develop a systematic, data-driven methodology for configuring MetaMap for optimal performance.

Methods

MetaMap, the word2vec model, and the phrase model were used to build a pipeline. For unsupervised training, the phrase and word2vec models used abstracts related to clinical decision support as input. During testing, MetaMap was configured with the default option, one behavior option, and two behavior options. For each configuration, cosine and soft cosine similarity scores between identified entities and gold-standard terms were computed for 40 annotated abstracts (422 sent

SUBMITTER: Jing X 

PROVIDER: S-EPMC9788913 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature