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Cited by 356AI in cancer detectionRadiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education

Artificial intelligence for digital and computational pathology

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Song, Andrew H., Jaume, Guillaume, Williamson, Drew F. K., Lu, Ming Y., Vaidya, Anurag, Miller, Tiffany R., Mahmood, Faisal·2023·Nature Reviews Bioengineering
DOI 10.1038/s44222-023-00096-8
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Cited by

Sorted by citations

Authors
Song, A. H., Jaume, G., Williamson, D. F. K., Lu, M. Y., Vaidya, A., Miller, T. R., & Mahmood, F.
Affiliations
  • Broad Institute (US)
  • Brigham and Women's Hospital (US)
Corresponding author
Mahmood, Faisal
ORCID
Venue
Nature Reviews Bioengineering
Publisher
Springer Science and Business Media LLC
Published
2023-10-02
Volume
1
Issue
12
Pages
930-949
ISSN
2731-6092 (ISSN-L)
DOI
10.1038/s44222-023-00096-8
OpenAlex
W4387259074
Cited by
356
References
36
Citations by year
2026: 135 · 2025: 152 · 2024: 66 · 2023: 3
FWCI
7.44
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Reviews Bioengineering (publishedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
computational pathology, digital pathology, whole slide images, deep learning, outcome prediction, treatment response prediction, morphological markers, clinical adoption of AI

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