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 …

Abstract The advent of Artificial Intelligence (AI) has resulted in development of novel
applications in a multitude of fields, such as in Medicine, to aid medical professionals in …

Background The Coronavirus disease 2019 (COVID-19) pandemic has affected millions of
people across the globe. It is associated with a high mortality rate and has created a global …

Natural language processing (NLP), which aims to convert human language into
expressions that can be analyzed by computers, is one of the most rapidly develo** and …

Background Accurate differentiation and prioritization in emergency department (ED) triage
is important to identify high-risk patients and to efficiently allocate of finite resources. Using …

Methods: A comprehensive literature collection was compiled through electronic
databases/internet search engines (PubMed, Web of Science Platform, MEDLINE, Scopus …

Introduction Natural language processing (NLP) uses various computational methods to
analyse and understand human language, and has been applied to data acquired at …

The depth and breadth of data produced in the modern cardiac intensive care unit (CICU)
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …

BACKGROUND In-field triage tools for trauma patients are limited by availability of
information, linear risk classification, and a lack of confidence reporting. We therefore set out …

Background Natural language processing has been established as an important tool when
using unstructured text data; however, most studies in the medical field have been limited to …