Hybrid Deep Learning for Medication-Related Information Extraction From Clinical Texts in French: MedExt Algorithm Development Study.

ABSTRACT:

Background

Information related to patient medication is crucial for health care; however, up to 80% of the information resides solely in unstructured text. Manual extraction is difficult and time-consuming, and there is not a lot of research on natural language processing extracting medical information from unstructured text from French corpora.

Objective

We aimed to develop a system to extract medication-related information from clinical text written in French.

Methods

We developed a hybrid system combining an expert rule-based system, contextual word embedding (embedding for language model) trained on clinical notes, and a deep recurrent neural network (bidirectional long short term memory-conditional random field). The task consisted of extracting drug mentions and

SUBMITTER: Jouffroy J 

PROVIDER: S-EPMC8077811 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature