An automated identification and analysis of ontological terms in gastrointestinal diseases and nutrition-related literature provides useful insights.

ABSTRACT: With an unprecedented growth in the biomedical literature, keeping up to date with the new developments presents an immense challenge. Publications are often studied in isolation of the established literature, with interpretation being subjective and often introducing human bias. With ontology-driven annotation of biomedical data gaining popularity in recent years and online databases offering metatags with rich textual information, it is now possible to automatically text-mine ontological terms and complement the laborious task of manual management, interpretation, and analysis of the accumulated literature with downstream statistical analysis. In this paper, we have formulated an automated workflow through which we have identified ontological information, including nutrition-related term

SUBMITTER: Koci O 

PROVIDER: S-EPMC6064635 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature