Objective To identify and synthesise research on applications of natural language
processing (NLP) for information extraction and retrieval from clinical notes in dentistry …

One stepping stone for reducing the maternal mortality is to identify severe maternal
morbidity (SMM) using Electronic Health Records (EHRs). We aim to develop a pipeline to …

Real-word errors are characterized by being actual terms in the dictionary. By providing
context, real-word errors are detected. Traditional methods to detect and correct such errors …

Background Textual corpora are extremely important for various NLP applications as they
provide information necessary for creating, setting and testing those applications and the …

The two fundamental tasks that a physician performs during every interaction with a patient
are reading and updating electronic health records (EHRs). Reading the records is …

Objective Suicide risk prediction algorithms at the Veterans Health Administration (VHA) do
not include predictors based on the 3-Step Theory of suicide (3ST), which builds on …

Background Unstructured text in medical records, such as Electronic Health Records,
contain an enormous amount of valuable information for research; however, it is difficult to …

Automatic spelling correction is one of the most important problems in natural language
processing. Its difficulty increases in medical corpora, due to the intrinsic particularities that …

This corpus-based study aimed to investigate the presence of context-dependent linguistic
errors in a corpus of clinical reports. The data were taken from a corpus comprising more …

The Madurese language lacks of spelling correction study. Spelling correction suggests a
list of corrections for misspelled words or strings. Its process consists of two steps, ie …