Multivariate Symptom Modeling

Multivariate Symptom Modeling is a statistical framework that simultaneously analyzes multiple interrelated symptoms to identify underlying patterns, interactions, and predictive relationships within a given clinical or population context.

11

Publications

548

Citations

50

Authors

37

Institutions

Publications per year

2017–2026

5

Authors

50

  1. XH
    Xiao‐Jun Huang

    Peking University, China

    1 publications · 17 citations

    1

    h-index

  2. WG
    William G Dixon

    University of Manchester, United Kingdom

    1 publications · 23 citations

    1

    h-index

  3. AB
    Andre B. Araujo

    New England Research Institutes, United States

    1 publications · 45 citations

    1

    h-index

  4. SC
    Shan Chen

    New England Research Institutes, United States

    1 publications · 45 citations

    1

    h-index

  5. OH
    Oliver Hirsch

    Philipps University of Marburg, Germany

    1 publications · 12 citations

    1

    h-index

1–5 of 50

Venues

  1. Addiction

    1 publications · 15 citations

    1

    h-index

  2. The Journal of Urology

    1 publications · 45 citations

    1

    h-index

  3. Medicine

    1 publications · 17 citations

    1

    h-index

  4. Medical Care

    1 publications · 68 citations

    1

    h-index

  5. Human Brain Mapping

    1 publications · 222 citations

    1

    h-index

1–5