Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

ABSTRACT:

Background

Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations.

Methods

We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied CLAMP, cTA

SUBMITTER: Peng J 

PROVIDER: S-EPMC7772897 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature