Computer-aided Tumor Grading

Computer-Aided Tumor Grading is a computational methodology that integrates image analysis algorithms and machine learning models to assist in the quantitative assessment and classification of tumor malignancy levels from histopathological or radiological data, thereby enhancing the objectivity and reproducibility of tumor grading in clinical decision-making.

351

Publications

17.6K

Citations

2.4K

Authors

920

Institutions

Publications per year

2017–2026

252

Authors

2.4K

  1. JK
    Jun Kong

    Emory University, United States

    8 publications · 506 citations

    8

    h-index

  2. AM
    Anant Madabhushi

    Case Western Reserve University, United States

    7 publications · 334 citations

    7

    h-index

  3. MN
    Metin N. Gürcan

    The Ohio State University, United States

    7 publications · 485 citations

    7

    h-index

  4. JV
    Jeroen van der Laak

    Radboud University Nijmegen, Netherlands

    6 publications · 882 citations

    6

    h-index

  5. OS
    Olcay Sertel

    The Ohio State University, United States

    6 publications · 452 citations

    6

    h-index

1–5 of 2.4K

Venues

  1. European Radiology

    15 publications · 668 citations

    13

    h-index

  2. PubMed

    Repository · 13 publications · 645 citations

    12

    h-index

  3. Scientific Reports

    9 publications · 554 citations

    9

    h-index

  4. Computers in Biology and Medicine

    9 publications · 822 citations

    9

    h-index

  5. Computer Methods and Programs in Biomedicine

    8 publications · 445 citations

    8

    h-index

1–5