Artificial Intelligence-based Planning

Artificial Intelligence-Based Planning is a computational decision-making framework within digital treatment planning that employs artificial intelligence algorithms to autonomously generate, optimize, or adapt clinical treatment strategies through data-driven learning and pattern recognition distinct from rule-based or manual planning approaches.

141

Publications

6.1K

Citations

559

Authors

266

Institutions

Publications per year

2017–2026

71

Authors

559

  1. SC
    Steve Chien

    Jet Propulsion Laboratory, United States

    4 publications · 56 citations

    4

    h-index

  2. FY
    F Yin

    Duke Medical Center, United States

    3 publications · 110 citations

    3

    h-index

  3. XL
    Xingyu Liu

    Peking University, China

    3 publications · 91 citations

    3

    h-index

  4. KM
    Kevin M. Passino

    The Ohio State University, United States

    3 publications · 75 citations

    3

    h-index

  5. MA
    Mohsen Asadi

    University of Saskatchewan, Canada

    2 publications · 85 citations

    2

    h-index

1–5 of 559

Venues

  1. AI Magazine

    5 publications · 602 citations

    5

    h-index

  2. IEEE Access

    3 publications · 309 citations

    3

    h-index

  3. Radiotherapy and Oncology

    2 publications · 61 citations

    2

    h-index

  4. 2

    h-index

  5. PubMed

    Repository · 2 publications · 82 citations

    2

    h-index

1–5