Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Jan Moritz Niehues"'
Autor:
Subarnarekha Chatterji, Jan Moritz Niehues, Marko van Treeck, Chiara Maria Lavinia Loeffler, Oliver Lester Saldanha, Gregory Patrick Veldhuizen, Didem Cifci, Zunamys Itzell Carrero, Rasha Abu-Eid, Valerie Speirs, Jakob Nikolas Kather
Publikováno v:
npj Breast Cancer, Vol 9, Iss 1, Pp 1-10 (2023)
Abstract Breast cancer prognosis and management for both men and women are reliant upon estrogen receptor alpha (ERα) and progesterone receptor (PR) expression to inform therapy. Previous studies have shown that there are sex-specific binding charac
Externí odkaz:
https://doaj.org/article/bdd8711bc54a4bd2b2acb26413598361
Autor:
Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader, Soroosh Tayebi Arasteh, Christoph Haarburger, Christiane Kuhl, Tianci Wang, Tianyu Han, Teresa Nolte, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract Although generative adversarial networks (GANs) can produce large datasets, their limited diversity and fidelity have been recently addressed by denoising diffusion probabilistic models, which have demonstrated superiority in natural image s
Externí odkaz:
https://doaj.org/article/d86a20b08d6d4d73b3035c5f2ff0fb9f
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
Autor:
Oliver Lester Saldanha, Chiara M. L. Loeffler, Jan Moritz Niehues, Marko van Treeck, Tobias P. Seraphin, Katherine Jane Hewitt, Didem Cifci, Gregory Patrick Veldhuizen, Siddhi Ramesh, Alexander T. Pearson, Jakob Nikolas Kather
Publikováno v:
npj Precision Oncology, Vol 7, Iss 1, Pp 1-5 (2023)
Abstract The histopathological phenotype of tumors reflects the underlying genetic makeup. Deep learning can predict genetic alterations from pathology slides, but it is unclear how well these predictions generalize to external datasets. We performed
Externí odkaz:
https://doaj.org/article/4f10e94592cb43cab9a2a2ce9a50b0d9
Autor:
Oliver Lester Saldanha, Chiara M. L. Loeffler, Jan Moritz Niehues, Marko van Treeck, Tobias P. Seraphin, Katherine Jane Hewitt, Didem Cifci, Gregory Patrick Veldhuizen, Siddhi Ramesh, Alexander T. Pearson, Jakob Nikolas Kather
The histopathological phenotype of tumors reflects the underlying genetic makeup. Deep learning can predict genetic alterations from tissue morphology, but it is unclear how well these predictions generalize to external datasets. Here, we present a d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d5e69de2befd9c1c7a037c4e7803937
https://doi.org/10.1101/2022.09.15.507455
https://doi.org/10.1101/2022.09.15.507455
Autor:
Jan Moritz Niehues, Philip Quirke, Nicholas P. West, Heike I. Grabsch, Marko van Treeck, Yoni Schirris, Gregory P. Veldhuizen, Gordon G.A. Hutchins, Susan D. Richman, Sebastian Foersch, Titus J. Brinker, Junya Fukuoka, Andrey Bychkov, Wataru Uegami, Daniel Truhn, Hermann Brenner, Alexander Brobeil, Michael Hoffmeister, Jakob Nikolas Kather
Publikováno v:
Cell Reports Medicine. 4:100980
Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other biomarkers with high performance and whether DL predictions genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96a71a995283a292289b233f01eec3e3
https://doi.org/10.1016/j.xcrm.2023.100980
https://doi.org/10.1016/j.xcrm.2023.100980