Who Cited It

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

2019 · Nature Medicine · 2,803 citations · 0 from inside this corpus

Gabriele Campanella, Matthew G. Hanna, Luke Geneslaw, Allen P. Miraflor, Vitor Werneck Krauss Silva low, Klaus J. Busam, Edi Brogi, Victor E. Reuter, David S. Klimstra, Thomas J. Fuchs

No abstract in the source record.

Clinical-grade computational pathology using weakly supervised deep learning on whole sli… (2019)Clinical-grade computational …ggplot2 (2016)ggplot2Automatic differentiation in PyTorch (2017)Automatic differentiation in …Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases … (2017)Diagnostic Assessment of Deep…Classification and mutation prediction from non–small cell lung cancer histopathology ima… (2018)Classification and mutation p…
4 of 4 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
ggplot2201633,962
Automatic differentiation in PyTorch201711,099
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases …20173,388
Classification and mutation prediction from non–small cell lung cancer histopathology ima…20182,987

Links

DOI · Open access copy · OpenAlex record

Topics

AI in cancer detectionComputer Science
Digital Imaging for Blood DiseasesComputer Science
Cell Image Analysis TechniquesBiochemistry, Genetics and Molecular Biology

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports10 author record(s) attached.
  • supports47 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:48+00:00.

sha256 46f669157f96ea35…