Positive Predictive Value Optimization

Positive Predictive Value Optimization is a methodological framework in statistical classification that systematically enhances the proportion of true positive predictions among all positive predictions by minimizing false positives while maintaining desired sensitivity levels.

11

Publications

281

Citations

54

Authors

31

Institutions

Publications per year

2017–2026

4

Authors

54

  1. PT
    Prasad Tadepalli

    Oregon State University, United States

    2 publications · 93 citations

    2

    h-index

  2. RS
    Robert S. Galen

    University of Georgia, United States

    2 publications · 93 citations

    2

    h-index

  3. SM
    Sholom M. Weiss

    Rutgers, The State University of New Jersey, United States

    2 publications · 93 citations

    2

    h-index

  4. ZS
    Zainab Samad

    Duke University, United States

    1 publications · 48 citations

    1

    h-index

  5. LL
    Lauren L. Katzen

    Population Council, United States

    1 publications · 22 citations

    1

    h-index

1–5 of 54

Venues

  1. PubMed

    Repository · 1 publications · 26 citations

    1

    h-index

  2. The Bone & Joint Journal

    BJJ · 1 publications · 11 citations

    1

    h-index

  3. European Heart Journal Supplements

    1 publications · 13 citations

    1

    h-index

  4. Journal of the American Society of Echocardiography

    JASE · 1 publications · 48 citations

    1

    h-index

  5. National Conference on Artificial Intelligence

    Conference · 1 publications · 22 citations

    1

    h-index

1–5