Background Recent advances in performance of natural language processing (NLP)
techniques have spurred wider use and more sophisticated applications of NLP in radiology …

Detecting negation and uncertainty is crucial for medical text mining applications; otherwise,
extracted information can be incorrectly identified as real or factual events. Although several …

Dialogue systems are widely used in AI to support timely and interactive communication with
users. We propose a general-purpose dialogue system architecture that leverages …

This paper provides an overview of SpRadIE, the Multilingual Information Extraction Task of
CLEF eHealth 2021 evaluation lab. The challenge targets information extraction from …

Objectives: This survey aims to provide an overview of the current state of biomedical and
clinical Natural Language Processing (NLP) research and practice in Languages other than …

Abstract Natural Language Processing (NLP) based on new deep learning technology is
contributing to the emergence of powerful solutions that help healthcare providers and …

Background: Scientific discovery progresses by exploring new and uncharted territory. More
specifically, it advances by a process of transforming unknown unknowns first into known …

Background Important clinical information of patients is present in unstructured free-text
fields of Electronic Health Records (EHRs). While this information can be extracted using …

Background The quality of communication between healthcare professionals (HCPs) and
patients affects health outcomes. Different coding systems have been developed to unravel …

BACKGROUND. Reported rates of recommendations for additional imaging (RAIs) in
radiology reports are low. Bidirectional encoder representations from transformers (BERT), a …