Predictive Drowning Models

Predictive Drowning Models is a computational framework designed to identify and quantify the likelihood of drowning incidents by integrating environmental, behavioral, and physiological risk factors within dynamically simulated aquatic scenarios.

4

Publications

131

Citations

20

Authors

20

Institutions

Publications per year

2017–2026

1

Authors

20

  1. PD
    Peter Dawes

    Royal National Lifeboat Institution, United Kingdom

    1 publications · 64 citations

    1

    h-index

  2. BS
    Bruno Simonnet

    Centre Hospitalier Universitaire de Bordeaux, France

    1 publications · 13 citations

    1

    h-index

  3. MM
    Marcos Mateus

    University of Lisbon, Portugal

    1 publications · 15 citations

    1

    h-index

  4. JJ
    Joost J.L.M. Bierens

    Amsterdam UMC Location Vrije Universiteit Amsterdam, Netherlands

    1 publications · 64 citations

    1

    h-index

  5. MT
    Mike Tipton

    University of Portsmouth, United Kingdom

    1 publications · 64 citations

    1

    h-index

1–5 of 20

Venues

  1. Injury Prevention

    1 publications · 13 citations

    1

    h-index

  2. Biological Conservation

    1 publications · 39 citations

    1

    h-index

  3. Australian Journal of Forensic Sciences

    1 publications · 15 citations

    1

    h-index

  4. The American Journal of Emergency Medicine

    AJEM · 1 publications · 64 citations

    1

    h-index

1–4