Increased Interest in Applying Data-Driven Methodologies to Study Atopic Dermatitis and Eczema
Five central themes of data-driven research that characterize the field of atopic dermatitis (AD) and eczema were identified in a recent study published in Clinical and Translational Allergy.
Researchers summarized the past and future of data-driven AD and eczema and identified areas in the field that would benefit from the applications of these methods in a systematic characterization of the field. Publications to March 17, 2021 that applied multivariate statistics (MS), artificial intelligence (AI), and Bayesian statistics (BS) to AD and eczema research from the SCOPUS database were gathered and a bibliometric analysis was performed. The Latent Dirichlet allocation (LDA) algorithm was used to explore the main topics in the publications.
The 5 key themes of data-driven research on AD and eczema are:
- Allergic comorbidities
- Image analysis and classification
- Quality of life and treatment response
- Risk factors and prevalence
“Research areas that could benefit from the application of data‐driven methods include the study of the pathogenesis of the condition and related risk factors, its disaggregation into validated subtypes, and personalised severity management and prognosis,” concluded the study authors. “We highlight BS as a new and promising approach in AD and eczema research,” they added.
Duverdier A, Custovic A, Tanaka RJ. Data-driven research on eczema: Systematic characterization of the field and recommendations for the future. Clin Transl Allergy. 2022;12(6):e12170. doi:10.1002/clt2.12170