Predictive Claims Modeling

Predictive Claims Modeling is a computational analytics framework within health insurance analytics that employs statistical and machine learning techniques to forecast the likelihood, cost, or risk profile of future insurance claims based on historical claims and patient data.

78

Publications

2.9K

Citations

321

Authors

160

Institutions

Publications per year

2017–2026

42

Authors

321

  1. MV
    Mario V. Wüthrich

    ETH Zurich, Switzerland

    5 publications · 246 citations

    5

    h-index

  2. YX
    Yang Xie

    The University of Texas Southwestern Medical Center, United States

    2 publications · 65 citations

    2

    h-index

  3. DC
    David C. Chang

    Massachusetts General Hospital, United States

    2 publications · 65 citations

    2

    h-index

  4. GS
    G. Schreier

    Austrian Institute of Technology, Austria

    2 publications · 65 citations

    2

    h-index

  5. SN
    Sandra Neubauer

    Austrian Institute of Technology, Austria

    2 publications · 65 citations

    2

    h-index

1–5 of 321

Venues

  1. Insurance Mathematics and Economics

    4 publications · 75 citations

    4

    h-index

  2. PubMed

    Repository · 3 publications · 61 citations

    3

    h-index

  3. Reliability Engineering & System Safety

    3 publications · 156 citations

    3

    h-index

  4. Risks

    3 publications · 183 citations

    3

    h-index

  5. SSRN Electronic Journal

    Repository · 3 publications · 271 citations

    3

    h-index

1–5