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2020 – today
- 2023
[i2]Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West, Jan Moritz Niehues, Gregory Patrick Veldhuizen, Philip Quirke, Heike Irmgard Grabsch, Piet A. van den Brandt, Gordon G. A. Hutchins, Susan D. Richman
, Tanwei Yuan, Rupert Langer, Josien Christina Anna Jenniskens, Kelly Offermans, Wolfram Müller, Richard Gray, Stephen B. Gruber, Joel K. Greenson, Gad Rennert, Joseph D. Bonner, Daniel Schmolze, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Michael Hoffmeister, Daniel Truhn, Julia A. Schnabel, Melanie Boxberg, Tingying Peng, Jakob Nikolas Kather:
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study. CoRR abs/2301.09617 (2023)
2010 – 2019
- 2018
- [c1]Padmaja Jonnalagedda, Daniel Schmolze, Bir Bhanu:
MVPNets: Multi-viewing Path Deep Learning Neural Networks for Magnification Invariant Diagnosis in Breast Cancer. BIBE 2018: 189-194 - 2016
- [j1]Sheida Nabavi, Daniel Schmolze, Mayinuer Maitituoheti, Sadhika Malladi, Andrew H. Beck:
EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes. Bioinform. 32(4): 533-541 (2016) - [i1]Humayun Irshad, Eun-Yeong Oh, Daniel Schmolze, Liza M. Quintana, Laura Collins, Rulla M. Tamimi, Andrew H. Beck:
Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method. CoRR abs/1606.06681 (2016)
Coauthor Index
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