Work

Uncovering Variations in Clinical Notes for NLP Modeling

Year: 2024

Type: book-chapter

Abstract: Clinical text contains rich patient information and has attracted much research interest in applying Natural Language Processing (NLP) tools to model it. In this study, we quantified and analyzed the textual characteristics of five common clinical note types using multiple measurements, including lexical-level features, semantic content, and grammaticality. We found there exist significant linguistic variations in different clinical note types, while some types tend to be more similar than others.

Source: Studies in health technology and informatics

DOI: 10.3233/shti231244

Authors: Jinghui Liu, Daniel Capurro, Anthony Nguyen, Karin Verspoor

Institutions: Commonwealth Scientific and Industrial Research Organisation, The University of Melbourne, RMIT University

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funders: Commonwealth Scientific and Industrial Research Organisation, Medical Research Council, National Health and Medical Research Council