Natural Language Mapping of Electrocardiogram Interpretations to a Standardized Ontology.

ABSTRACT:

Background

Interpretations of the electrocardiogram (ECG) are often prepared using software outside the electronic health record (EHR) and imported via an interface as a narrative note. Thus, natural language processing is required to create a computable representation of the findings. Challenges include misspellings, nonstandard abbreviations, jargon, and equivocation in diagnostic interpretations.

Objectives

Our objective was to develop an algorithm to reliably and efficiently extract such information and map it to the standardized ECG ontology developed jointly by the American Heart Association, the American College of Cardiology Foundation, and the Heart Rhythm Society. The algorithm was to be designed to be easily modifiable for use with EHRs and ECG reporting systems o

SUBMITTER: Epstein RH 

PROVIDER: S-EPMC8595771 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature