Risk Stratification Model Interpretability

Risk Stratification Model Interpretability is a risk stratification model contribution that belongs to the class of interpretability methods and is differentiated by its focus on enabling transparent, understandable, and clinically meaningful explanations of how risk scores are derived and assigned within risk stratification models.

20

Publications

1K

Citations

222

Authors

92

Institutions

Publications per year

2017–2026

9

Authors

222

  1. EE
    Elif Eyigöz

    IBM Research - Thomas J. Watson Research Center, United States

    1 publications · 26 citations

    1

    h-index

  2. YP
    Yong Park

    Korea University, South Korea

    1 publications · 11 citations

    1

    h-index

  3. RA
    Robert A. Kyle

    Mayo Clinic, United States

    1 publications · 27 citations

    1

    h-index

  4. AG
    Alex Gatt

    Mater Dei Hospital, Malta

    1 publications · 49 citations

    1

    h-index

  5. FC
    Franco Casazza

    Ospedale San Carlo, Italy

    1 publications · 90 citations

    1

    h-index

1–5 of 222

Venues

  1. Artificial Intelligence in Medicine

    AIM · 2 publications · 64 citations

    2

    h-index

  2. Frontiers in Medicine

    1 publications · 41 citations

    1

    h-index

  3. European Journal of Cancer

    1 publications · 31 citations

    1

    h-index

  4. Annals of Allergy Asthma & Immunology

    ACAAI · 1 publications · 10 citations

    1

    h-index

  5. British Journal of Haematology

    BJH · 1 publications · 49 citations

    1

    h-index

1–5