Towards a practical use of text mining approaches in electrodiagnostic data.

ABSTRACT: Healthcare professionals produce abounding textual data in their daily clinical practice. Text mining can yield valuable insights from unstructured data. Extracting insights from multiple information sources is a major challenge in computational medicine. In this study, our objective was to illustrate how combining text mining techniques with statistical methodologies can yield new insights and contribute to the development of neurological and neuromuscular-related health information. We demonstrate how to utilize and derive knowledge from medical text, identify patient groups with similar diagnostic attributes, and examine differences between groups using demographical data and past medical history (PMH). We conducted a retrospective study for all patients who underwent electrodiagnostic

SUBMITTER: Ramon-Gonen R 

PROVIDER: S-EPMC10636146 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature