Whole-population Analytics

Whole-Population Analytics is a systematic analytical framework that enables comprehensive, data-driven insights across an entire population by integrating and analyzing diverse health-related datasets to identify patterns, risks, and outcomes at the population level, distinguishing itself from subset-focused or sample-based approaches through its inclusive scope and emphasis on holistic health determinants.

10

Publications

555

Citations

64

Authors

41

Institutions

Publications per year

2017–2026

6

Authors

64

  1. LB
    Liane Belland

    McGill University, Canada

    1 publications · 22 citations

    1

    h-index

  2. MM
    Michael McDuffie

    Harvard University, United States

    1 publications · 194 citations

    1

    h-index

  3. JV
    Jan van der Laan

    National Institute for Public Health and the Environment, Netherlands

    1 publications · 40 citations

    1

    h-index

  4. IC
    Innie Chen

    University of Ottawa, Canada

    1 publications · 22 citations

    1

    h-index

  5. DM
    David M. Maahs

    Stanford University, United States

    1 publications · 26 citations

    1

    h-index

1–5 of 64

Venues

  1. Bioinformatics

    1 publications · 57 citations

    1

    h-index

  2. QUT ePrints (Queensland University of Technology)

    Repository · 1 publications · 20 citations

    1

    h-index

  3. Big Data

    1 publications · 155 citations

    1

    h-index

  4. JMIR Diabetes

    1 publications · 26 citations

    1

    h-index

  5. Journal of Minimally Invasive Gynecology

    1 publications · 22 citations

    1

    h-index

1–5