Constructing a disease database and using natural language processing to capture and standardize free text clinical information.

ABSTRACT: The ability to extract critical information about an infectious disease in a timely manner is critical for population health research. The lack of procedures for mining large amounts of health data is a major impediment. The goal of this research is to use natural language processing (NLP) to extract key information (clinical factors, social determinants of health) from free text. The proposed framework describes database construction, NLP modules for locating clinical and non-clinical (social determinants) information, and a detailed evaluation protocol for evaluating results and demonstrating the effectiveness of the proposed framework. The use of COVID-19 case reports is demonstrated for data construction and pandemic surveillance. The proposed approach outperforms benchmark methods in

SUBMITTER: Raza S 

PROVIDER: S-EPMC10215040 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature