Stable Feature Identification

Stable Feature Identification is a methodological process within feature stability analysis that distinguishes itself by systematically detecting and validating features exhibiting consistent relevance or significance across varying conditions, datasets, or model perturbations to ensure robustness and generalizability in predictive modeling.

27

Publications

1.3K

Citations

101

Authors

56

Institutions

Publications per year

2017–2026

14

Authors

101

  1. LA
    Laura Arnal

    Universidad Nacional de La Plata, Argentina

    1 publications · 10 citations

    1

    h-index

  2. JR
    J. Ramón Navarro-Cerdán

    Universitat Politècnica de València, Spain

    1 publications · 10 citations

    1

    h-index

  3. XF
    Xueqiang Fan

    Hefei University of Technology, China

    1 publications · 35 citations

    1

    h-index

  4. DS
    Debajyoti Sinha

    Florida State University, United States

    1 publications · 57 citations

    1

    h-index

  5. ES
    Ekaterini S. Bei

    Technical University of Crete, Greece

    1 publications · 23 citations

    1

    h-index

1–5 of 101

Venues

  1. Computers in Biology and Medicine

    2 publications · 80 citations

    2

    h-index

  2. 1

    h-index

  3. Medical & Biological Engineering & Computing

    1 publications · 230 citations

    1

    h-index

  4. BMC Medical Genomics

    1 publications · 144 citations

    1

    h-index

  5. Information Fusion

    1 publications · 121 citations

    1

    h-index

1–5