Zobrazeno 1 - 10
of 856
pro vyhledávání: '"Zlobec, P."'
Autor:
Hung-Chang Chen, Nico Mueller, Katherine Stott, Chrysa Kapeni, Eilidh Rivers, Carolin M Sauer, Flavio Beke, Stephen J Walsh, Nicola Ashman, Louise O’Brien, Amir Rafati Fard, Arman Ghodsinia, Changtai Li, Fadwa Joud, Olivier Giger, Inti Zlobec, Ioana Olan, Sarah J Aitken, Matthew Hoare, Richard Mair, Eva Serrao, James D Brenton, Alicia Garcia-Gimenez, Simon E Richardson, Brian Huntly, David R Spring, Mikkel-Ole Skjoedt, Karsten Skjødt, Marc de la Roche, Maike de la Roche
Publikováno v:
EMBO Molecular Medicine, Vol 16, Iss 9, Pp 2233-2261 (2024)
Abstract We have developed and validated a highly specific, versatile antibody to the extracellular domain of human LGR5 (α-LGR5). α-LGR5 detects LGR5 overexpression in >90% of colorectal cancer (CRC), hepatocellular carcinoma (HCC) and pre-B-ALL t
Externí odkaz:
https://doaj.org/article/4df981d9b6cb481e9115536caaf2c410
Autor:
Hannah L. Williams, Ana Leni Frei, Thibaud Koessler, Martin D. Berger, Heather Dawson, Olivier Michielin, Inti Zlobec
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-18 (2024)
Abstract Enabling the examination of cell-cell relationships in tissue, spatially resolved omics technologies have revolutionised our perspectives on cancer biology. Clinically, the development of immune checkpoint inhibitors (ICI) has advanced cance
Externí odkaz:
https://doaj.org/article/f2ef085cd2a340bbb4523c525e173237
Autor:
Neto, Pedro C., Montezuma, Diana, Oliveira, Sara P., Oliveira, Domingos, Fraga, João, Monteiro, Ana, Monteiro, João, Ribeiro, Liliana, Gonçalves, Sofia, Reinhard, Stefan, Zlobec, Inti, Pinto, Isabel M., Cardoso, Jaime S.
Publikováno v:
npj Precis. Onc. 8, 56 (2024)
Considering the profound transformation affecting pathology practice, we aimed to develop a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-slide images (WSI). For this, we propose a deep learning (DL) system tha
Externí odkaz:
http://arxiv.org/abs/2301.02608
Autor:
Pedro C. Neto, Diana Montezuma, Sara P. Oliveira, Domingos Oliveira, João Fraga, Ana Monteiro, João Monteiro, Liliana Ribeiro, Sofia Gonçalves, Stefan Reinhard, Inti Zlobec, Isabel M. Pinto, Jaime S. Cardoso
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-15 (2024)
Abstract Considering the profound transformation affecting pathology practice, we aimed to develop a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-slide images (WSI). For this, we propose a deep learning (DL) s
Externí odkaz:
https://doaj.org/article/91253dbe2b0841d8ae5dbc0c4080a147
Autor:
Rumberger, Josef Lorenz, Baumann, Elias, Hirsch, Peter, Janowczyk, Andrew, Zlobec, Inti, Kainmueller, Dagmar
We describe here the panoptic segmentation method we devised for our participation in the CoNIC: Colon Nuclei Identification and Counting Challenge at ISBI 2022. Key features of our method are a weighted loss specifically engineered for semantic segm
Externí odkaz:
http://arxiv.org/abs/2203.11692
Due to the heterogeneity of real-world data, the widely accepted independent and identically distributed (IID) assumption has been criticized in recent studies on causality. In this paper, we argue that instead of being a questionable assumption, IID
Externí odkaz:
http://arxiv.org/abs/2203.00332
Autor:
Abbet, Christian, Studer, Linda, Fischer, Andreas, Dawson, Heather, Zlobec, Inti, Bozorgtabar, Behzad, Thiran, Jean-Philippe
Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome t
Externí odkaz:
http://arxiv.org/abs/2108.09178
Autor:
Jonathan TC Liu, Sarah SL Chow, Richard Colling, Michelle R Downes, Xavier Farré, Peter Humphrey, Andrew Janowczyk, Tuomas Mirtti, Clare Verrill, Inti Zlobec, Lawrence D True
Publikováno v:
The Journal of Pathology: Clinical Research, Vol 10, Iss 1, Pp n/a-n/a (2024)
Abstract In recent years, technological advances in tissue preparation, high‐throughput volumetric microscopy, and computational infrastructure have enabled rapid developments in nondestructive 3D pathology, in which high‐resolution histologic da
Externí odkaz:
https://doaj.org/article/ae2382569a7a4659b6ce5953678b78d0
With the long-term rapid increase in incidences of colorectal cancer (CRC), there is an urgent clinical need to improve risk stratification. The conventional pathology report is usually limited to only a few histopathological features. However, most
Externí odkaz:
http://arxiv.org/abs/2007.03292
Autor:
Joe Yeong, Bernett Lee, Inti Zlobec, Jeffrey Lim, Mai Chan Lau, Felicia Wee, Chan Way Ng, Xinyun Feng, Marcia Zhang, Willa Yim, Menaka Priyadharsani Rajapakse, Olaf Rotzchke
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 11, Iss Suppl 1 (2023)
Externí odkaz:
https://doaj.org/article/8874c5a196ff4377858254b151b596a6