Decision Threshold Optimization

Decision Threshold Optimization is a Bayesian diagnostic method that systematically determines the optimal cutoff point for classifying posterior probabilities by balancing misclassification costs and diagnostic accuracy within decision-theoretic frameworks.

146

Publications

5.9K

Citations

427

Authors

208

Institutions

Publications per year

2017–2026

42

Authors

427

  1. CV
    Chi‐Man Vong

    University of Macau, Macao SAR China

    3 publications · 115 citations

    3

    h-index

  2. YL
    Youming Li

    Ningbo University, China

    3 publications · 74 citations

    3

    h-index

  3. MJ
    Ming Jin

    Ningbo University, China

    3 publications · 74 citations

    3

    h-index

  4. ZT
    Zefan Tang

    University of Connecticut, United States

    2 publications · 163 citations

    2

    h-index

  5. SG
    Shimin Gong

    Sun Yat-sen University, China

    2 publications · 31 citations

    2

    h-index

1–5 of 427

Venues

  1. IEEE Communications Letters

    4 publications · 111 citations

    4

    h-index

  2. IEEE Transactions on Information Theory

    4 publications · 207 citations

    4

    h-index

  3. Journal of Chemical Information and Modeling

    JCIM · 2 publications · 197 citations

    2

    h-index

  4. IEEE Transactions on NanoBioscience

    2 publications · 52 citations

    2

    h-index

  5. IEEE Wireless Communications Letters

    2 publications · 89 citations

    2

    h-index

1–5