Building a semantically annotated corpus for chronic disease complications using two document types.

ABSTRACT: Narrative information in electronic health records (EHRs) contains a wealth of information related to patient health conditions. In addition, people use Twitter to express their experiences regarding personal health issues, such as medical complaints, symptoms, treatments, lifestyle, and other factors. Both genres of text include different types of health-related information concerning disease complications and risk factors. Knowing detailed information about controlling disease risk factors has a great impact on modifying these risks and subsequently preventing disease complications. Text-mining tools provide efficient solutions to extract and integrate vital information related to disease complications hidden in the large volume of the narrative text. However, the development of text-min

SUBMITTER: Alnazzawi N 

PROVIDER: S-EPMC7971867 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature