Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies.

ABSTRACT:

Background

Free-text descriptions in electronic health records (EHRs) can be of interest for clinical research and care optimization. However, free text cannot be readily interpreted by a computer and, therefore, has limited value. Natural Language Processing (NLP) algorithms can make free text machine-interpretable by attaching ontology concepts to it. However, implementations of NLP algorithms are not evaluated consistently. Therefore, the objective of this study was to review the current methods used for developing and evaluating NLP algorithms that map clinical text fragments onto ontology concepts. To standardize the evaluation of algorithms and reduce heterogeneity between studies, we propose a list of recommendations.

Methods

Two reviewers examined publications indexe

SUBMITTER: Kersloot MG 

PROVIDER: S-EPMC7670625 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature