Artificial Intelligence-based Screening

Artificial Intelligence-Based Screening is a computational methodology that employs machine learning and pattern recognition algorithms to analyze biomedical data for the early identification of malignant abnormalities, distinguishing itself from conventional screening techniques through automated, data-driven prediction models that improve accuracy, scalability, and speed in detecting cancer at preclinical stages.

616

Publications

41.7K

Citations

4.4K

Authors

1.7K

Institutions

Publications per year

2017–2026

547

Authors

4.4K

  1. KL
    Kristina Lång

    Skåne University Hospital, Sweden

    10 publications · 1.9K citations

    10

    h-index

  2. CI
    Christoph I. Lee

    University of Washington, United States

    10 publications · 542 citations

    10

    h-index

  3. AR
    Alejandro Rodríguez‐Ruiz

    Radboud University Nijmegen, Netherlands

    10 publications · 2.2K citations

    10

    h-index

  4. SH
    Solveig Hofvind

    Cancer Registry of Norway, Norway

    9 publications · 1K citations

    9

    h-index

  5. AR
    Alessandro Repici

    Humanitas University, Italy

    8 publications · 669 citations

    8

    h-index

1–5 of 4.4K

Venues

  1. Radiology

    15 publications · 1.7K citations

    15

    h-index

  2. Scientific Reports

    13 publications · 788 citations

    13

    h-index

  3. European Radiology

    12 publications · 797 citations

    12

    h-index

  4. IEEE Access

    9 publications · 2.4K citations

    9

    h-index

  5. Frontiers in Oncology

    8 publications · 190 citations

    8

    h-index

1–5