Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.

ABSTRACT:

Background

In recent years, health data collected during the clinical care process have been often repurposed for secondary use through clinical data warehouses (CDWs), which interconnect disparate data from different sources. A large amount of information of high clinical value is stored in unstructured text format. Natural language processing (NLP), which implements algorithms that can operate on massive unstructured textual data, has the potential to structure the data and make clinical information more accessible.

Objective

The aim of this review was to provide an overview of studies applying NLP to textual data from CDWs. It focuses on identifying the (1) NLP tasks applied to data from CDWs and (2) NLP methods used to tackle these tasks.

Methods

This review was p

SUBMITTER: Bazoge A 

PROVIDER: S-EPMC10757232 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature