Registry Data Modeling

Registry Data Modeling is a clinical data modeling approach that systematically defines the structure, metadata, and standards for collecting, managing, and representing data within clinical registries to support longitudinal observation, regulatory compliance, and comparative effectiveness research.

52

Publications

2K

Citations

323

Authors

170

Institutions

Publications per year

2017–2026

24

Authors

323

  1. RH
    Ruth H. Keogh

    London School of Hygiene & Tropical Medicine, United Kingdom

    2 publications · 45 citations

    2

    h-index

  2. JA
    Jiye An

    Zhejiang University, China

    2 publications · 70 citations

    2

    h-index

  3. SC
    S.B. Carr

    Royal Brompton Hospital, United Kingdom

    2 publications · 45 citations

    2

    h-index

  4. XL
    Xudong Lü

    Zhejiang University, China

    2 publications · 70 citations

    2

    h-index

  5. LM
    Lingtong Min

    Northwestern Polytechnical University, China

    2 publications · 70 citations

    2

    h-index

1–5 of 323

Venues

  1. American Journal of Transplantation

    2 publications · 51 citations

    2

    h-index

  2. Statistics in Medicine

    2 publications · 41 citations

    2

    h-index

  3. PubMed

    Repository · 2 publications · 42 citations

    2

    h-index

  4. Computer Methods and Programs in Biomedicine

    2 publications · 40 citations

    2

    h-index

  5. Pediatric Diabetes

    1 publications · 15 citations

    1

    h-index

1–5