Artificial intelligence in histopathology: enhancing cancer research and clinical oncology
By Artem Shmatko, N. Ghaffari Laleh, Moritz Gerstung, Jakob Nikolas Kather. Nature Cancer, 2022
405 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Oncology, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/d7524f2ec8ad9866190c1b2d030fcac95cc3f565
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Faisal Mahmood
- Ming Y. Lu
- Drew F. K. Williamson
- Angela Zhang
- James Y. Zou
- Ash A. Alizadeh
- Kyle Swanson
- Eric Wu
In Oncology
In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment. (2023, methodology): “Advances in ML for computer vision have been adapted for medical imaging and are already showing great promise for rapidly and accurately analyzing a variety of imaging modalities in clinical oncology.(6,7) Although imaging informs many aspects of cancer care, molecular characterization can provide ”
- Artificial intelligence for digital and computational pathology (2023, background): “P a t c h i m p o r t a n c e”