Radiological reporting has generated large quantities of digital content within the electronic
health record, which is potentially a valuable source of information for improving clinical care …

Motivation Annotation tools are applied to build training and test corpora, which are
essential for the development and evaluation of new natural language processing …

Background Natural language processing applied to clinical text or aimed at a clinical
outcome has been thriving in recent years. This paper offers the first broad overview of …

Objective: To perform a review of recent research in clinical data reuse or secondary use,
and envision future advances in this field. Methods: The review is based on a large literature …

The migration of imaging reports to electronic medical record systems holds great potential
in terms of advancing radiology research and practice by leveraging the large volume of …

Diagnostic imaging reports are generally written with a target audience of other providers.
As a result, the reports are written with medical jargon and technical detail to ensure …

Background Extracting information from free texts using natural language processing (NLP)
can save time and reduce the hassle of manually extracting large quantities of data from …

Artificial Intelligence and machine-learning (ML) studies are increasingly populating the life
science space and some have also started to integrate certain clinical decision support …

Abstract Machine learning models for radiology benefit from large-scale data sets with high
quality labels for abnormalities. We curated and analyzed a chest computed tomography …

Abstract The Breast Imaging Reporting and Data System (BI-RADS) was developed to
reduce variation in the descriptions of findings. Manual analysis of breast radiology report …