Make deep learning algorithms in computational pathology more reproducible and reusable
Sophia J. Wagner(Brigham and Women's Hospital), Tingying Peng(Helmholtz Zentrum München), Ario Sadafi(Helmholtz Munich), Sayedali Shetab Boushehri(Roche (Sweden)), Lorenz Lamm(University of Basel), Carsten Marr(German Cancer Research Center), Christian Matek(Friedrich-Alexander-Universität Erlangen-Nürnberg), Dominik Waibel(Helmholtz Munich), Melanie Boxberg(Starnberg Hospital)
Cited by 25
Related Papers
The future landscape of large language models in medicine
|Communications Medicine|2023|937
Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study
|Cancer Cell|2023|262
Tumour budding activity and cell nest size determine patient outcome in oral squamous cell carcinoma: proposal for an adjusted grading system
|Histopathology|2017|105
PD-L1 and PD-1 and characterization of tumor-infiltrating lymphocytes in high grade sarcomas of soft tissue – prognostic implications and rationale for immunotherapy
|OncoImmunology|2017|89
Composition and Clinical Impact of the Immunologic Tumor Microenvironment in Oral Squamous Cell Carcinoma
|The Journal of Immunology|2018|81