Performance of Natural Language Processing for Information Extraction From Electronic Health Records Within Cancer: Systematic Review.

ABSTRACT:

Background

Over the last decade, natural language processing (NLP) has provided various solutions for information extraction (IE) from textual clinical data. In recent years, the use of NLP in cancer research has gained considerable attention, with numerous studies exploring the effectiveness of various NLP techniques for identifying and extracting cancer-related entities from clinical text data.

Objective

We aimed to summarize the performance differences between various NLP models for IE within the context of cancer to provide an overview of the relative performance of existing models.

Methods

This systematic literature review was conducted using 3 databases (PubMed, Scopus, and Web of Science) to search for articles extracting cancer-related entities from clinical t

SUBMITTER: Dahl S 

PROVIDER: S-EPMC12431712 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature