Adaptive Algorithms Regulation

Adaptive Algorithms Regulation is a regulatory framework that governs the development, validation, and deployment of machine learning algorithms in digital health devices, distinguished by its requirement for continuous monitoring, real-world performance assessment, and iterative updates to ensure safety, efficacy, and compliance as the algorithm evolves over time.

6

Publications

910

Citations

19

Authors

16

Institutions

Publications per year

2017–2026

5

Authors

19

  1. VM
    V. Morino

    University of Genoa, Italy

    1 publications · 120 citations

    1

    h-index

  2. CM
    Catherine M. Sharkey

    New York University, United States

    1 publications · 26 citations

    1

    h-index

  3. MM
    Meghavi Mashar

    University of Cambridge, United Kingdom

    1 publications · 20 citations

    1

    h-index

  4. CS
    Carlo S. Regazzoni

    University of Genoa, Italy

    1 publications · 120 citations

    1

    h-index

  5. NS
    Nicholas S. Peters

    Imperial College London, United Kingdom

    1 publications · 20 citations

    1

    h-index

1–5 of 19

Venues

  1. Science and Technology Law Review

    1 publications · 26 citations

    1

    h-index

  2. Regulation & Governance

    1 publications · 648 citations

    1

    h-index

  3. Nature Medicine

    1 publications · 15 citations

    1

    h-index

  4. Journal of Medical Internet Research

    1 publications · 81 citations

    1

    h-index

  5. JMIR AI

    1 publications · 20 citations

    1

    h-index

1–5