Semantic search helper: A tool based on the use of embeddings in multi-item questionnaires as a harmonization opportunity for merging large datasets - A feasibility study.

ABSTRACT:

Background

Recent advances in natural language processing (NLP), particularly in language processing methods, have opened new avenues in semantic data analysis. A promising application of NLP is data harmonization in questionnaire-based cohort studies, where it can be used as an additional method, specifically when only different instruments are available for one construct as well as for the evaluation of potentially new construct-constellations. The present article therefore explores embedding models' potential to detect opportunities for semantic harmonization.

Methods

Using models like SBERT and OpenAI's ADA, we developed a prototype application ("Semantic Search Helper") to facilitate the harmonization process of detecting semantically similar items within extensive heal

SUBMITTER: Gottfried K 

PROVIDER: S-EPMC11795448 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature