Diagnostic Summary Generation

Diagnostic Summary Generation is a computational method that synthesizes observed anomalies, contextual data, and inferred causal relationships into a concise, structured report to support decision-making in problem-solving domains.

13

Publications

381

Citations

41

Authors

19

Institutions

Publications per year

2017–2026

1

Authors

41

  1. NG
    Nicholas G. Polson

    University of Chicago, United States

    2 publications · 59 citations

    2

    h-index

  2. CC
    Cinzia Carota

    University of Chicago, United States

    2 publications · 59 citations

    2

    h-index

  3. GP
    Giovanni Parmigiani

    Johns Hopkins University, United States

    2 publications · 59 citations

    2

    h-index

  4. YW
    Yuan Wu

    Duke University, United States

    1 publications · 26 citations

    1

    h-index

  5. RK
    Ravi Kapadia

    General Atomics (United States), United States

    1 publications · 24 citations

    1

    h-index

1–5 of 41

Venues

  1. 2

    h-index

  2. Bioinformatics

    1 publications · 26 citations

    1

    h-index

  3. Systems Research and Behavioral Science

    1 publications · 14 citations

    1

    h-index

  4. Alzheimer Disease & Associated Disorders

    ADAD · 1 publications · 31 citations

    1

    h-index

  5. Distributed Computing

    1 publications · 13 citations

    1

    h-index

1–5