Objectives To provide an overview and tutorial of natural language processing (NLP) and
modern NLP-system design. Target audience This tutorial targets the medical informatics …

With the widespread adoption of electronic health records (EHRs), large repositories of
structured and unstructured patient data are becoming available to conduct observational …

Objective Clinical documents made available for secondary use play an increasingly
important role in discovery of clinical knowledge, development of research methods, and …

Narrative reports in medical records contain a wealth of information that may augment
structured data for managing patient information and predicting trends in diseases. Pertinent …

Sentiment classification concerns the use of automatic methods for predicting the orientation
of subjective content on text documents, with applications on a number of areas including …

In this paper we describe an algorithm called ConText for determining whether clinical
conditions mentioned in clinical reports are negated, hypothetical, historical, or experienced …

The introduction and rapid growth of the Internet of Medical Things (IoMT), a subset of the
Internet of Things (IoT) in the medical and healthcare systems, has brought numerous …

Abstract Information extraction (IE), a natural language processing (NLP) task that
automatically extracts structured or semi-structured information from free text, has become …

Traditionally, most research in NLP has focused on propositional aspects of meaning. To
truly understand language, however, extra-propositional aspects are equally important …

Abstract In Electronic Health Records (EHRs), much of valuable information regarding
patients' conditions is embedded in free text format. Natural language processing (NLP) …