Use of unstructured text in prognostic clinical prediction models: a systematic review.

ABSTRACT:

Objective

This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether using text data in addition to more commonly used structured data improves the prediction performance.

Materials and methods

We searched Embase, MEDLINE, Web of Science, and Google Scholar to identify studies that developed prognostic prediction models using information extracted from unstructured text in a data-driven manner, published in the period from January 2005 to March 2021. Data items were extracted, analyzed, and a meta-analysis of the model performance was carried out to assess the added value of text to structured-data mo

SUBMITTER: Seinen TM 

PROVIDER: S-EPMC9196702 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature