Artificial Intelligence Transparency

Artificial Intelligence Transparency is a methodological framework within digital health research ethics that ensures the processes, data, and decision-making mechanisms of artificial intelligence systems are accessible, interpretable, and accountable to stakeholders, thereby enabling informed scrutiny and ethical governance.

573

Publications

47.8K

Citations

1.6K

Authors

807

Institutions

Publications per year

2017–2026

570

Authors

1.6K

  1. JW
    Judy Wawira Gichoya

    Emory University, United States

    5 publications · 730 citations

    5

    h-index

  2. EK
    Elmar Kotter

    University Medical Center Freiburg, Germany

    4 publications · 679 citations

    4

    h-index

  3. JP
    John P. A. Ioannidis

    Stanford University, United States

    4 publications · 535 citations

    4

    h-index

  4. LA
    Leo Anthony Celi

    Beth Israel Deaconess Medical Center, United States

    3 publications · 143 citations

    4

    h-index

  5. SL
    Stefan Larsson

    Lund University, Sweden

    3 publications · 514 citations

    4

    h-index

1–5 of 1.6K

Venues

  1. arXiv (Cornell University)

    Repository · 17 publications · 1.1K citations

    17

    h-index

  2. SSRN Electronic Journal

    Repository · 22 publications · 1.7K citations

    15

    h-index

  3. AI and Ethics

    11 publications · 755 citations

    14

    h-index

  4. AI & Society

    13 publications · 1K citations

    13

    h-index

  5. PLOS Digital Health

    4 publications · 301 citations

    7

    h-index

1–5