Enabling data linkages for rare diseases in a resilient environment with the SERDIF framework.
| Autor: | Navarro-Gallinad, Albert, Orlandi, Fabrizio, Scott, Jennifer, Havyarimana, Enock, Basu, Neil, Little, Mark A., O'Sullivan, Declan |
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VASCULITIS
RISK assessment PREDICTION models DATABASE management INTERPROFESSIONAL relations TASK performance LABOR productivity COMPUTER software QUALITATIVE research RESEARCH funding RARE diseases CLIMATE change QUESTIONNAIRES PREMATURE infants MEDICAL record linkage QUANTITATIVE research REPORTING of diseases ULTRAVIOLET radiation SURVEYS EXPERIMENTAL design JOB satisfaction THEMATIC analysis ELECTRONIC data interchange VIDEOCONFERENCING METADATA EPIDEMIOLOGISTS USER-centered system design CASE studies DISEASE relapse USER interfaces DISEASE risk factors |
| Zdroj: | NPJ Digital Medicine; 10/4/2024, Vol. 7 Issue 1, p1-9, 9p |
| Abstrakt: | Environmental factors amplified by climate change contribute significantly to the global burden of disease, disproportionately impacting vulnerable populations, such as individuals with rare diseases. Researchers require innovative, dynamic data linkage methods to enable the development of risk prediction models, particularly for diseases like vasculitis with unknown aetiology but potential environmental triggers. In response, we present the Semantic Environmental and Rare Disease Data Integration Framework (SERDIF). SERDIF was evaluated with researchers studying climate-related health hazards of vasculitis disease activity across European countries (N |
| Databáze: | Complementary Index |
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