Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …

Background Natural language processing (NLP) has a significant role in advancing
healthcare and has been found to be key in extracting structured information from radiology …

Process of information extraction (IE) is used to extract useful information from unstructured
or semi-structured data. Big data arise new challenges for IE techniques with the rapid …

Much of the knowledge and information needed for enabling high-quality clinical research is
stored in free-text format. Natural language processing (NLP) has been used to extract …

Electronic health records (EHR) contain large volumes of unstructured text, requiring the
application of information extraction (IE) technologies to enable clinical analysis. We present …

To eliminate security attack risks of software products, the security bug report (SBR)
prediction has been increasingly investigated. However, there is still much room for …

As great amounts of food-related information is presented in the form of heterogeneous
textual data, computer-based methods are useful to automatically extract such information …

Named entity recognition (NER) is a key component of many scientific literature mining
tasks, such as information retrieval, information extraction, and question answering; …

Background Accurate and timely detection of medical adverse events (AEs) from free-text
medical narratives can be challenging. Natural language processing (NLP) with deep …

This paper presents a new corpus of radiology medical reports written in Spanish and
labeled with ICD-10. CARES (Corpus of Anonymised Radiological Evidences in Spanish) is …