Peer-Reviewed Publication
JMIR Form Res2025;9e75608.August 27, 2025Journal Article

Automated Data Harmonization in Clinical Research: Natural Language Processing Approach.

Pratheek Mallya1, Ricardo Henao2, Chuan Hong2, Daniel Wojdyla3, Tony Schibler3, Vihaan Manchanda1, Michael Pencina2, Jennifer Hall1, Juan Zhao1
1American Heart Association, 7272 Greenville Ave, Dallas, TX, 75231, United States, 1 2147061164.
2Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, United States.
3Duke Clinical Research Institute, Durham, NC, United States.

Abstract

BACKGROUND: Integrating data is essential for advancing clinical and epidemiological research. However, because datasets often describe variables (eg, demographic and health conditions) in diverse ways, the process of integrating and harmonizing variables from research studies remains a major bottleneck. OBJECTIVE: The objective was to assess a natural language processing-based method to automate…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.