Swarm learning for decentralized artificial intelligence in cancer histopathology
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: 10.1038/s41591-022-01768-5
- Ereignis
-
Veröffentlichung
- (wo)
-
Aachen
- (wer)
-
Universitätsbibliothek der RWTH Aachen
- (wann)
-
2022
- Urheber
-
Saldanha, Oliver Lester
Quirke, Philip
West, Nicholas P.
James, Jacqueline A.
Loughrey, Maurice B.
Grabsch, Heike I.
Salto-Tellez, Manuel
Alwers, Elizabeth
Cifci, Didem
Ghaffari Laleh, Narmin
Seibel, Tobias
Gray, Richard
Hutchins, Gordon G. A.
Brenner, Hermann
van Treeck, Marko
Yuan, Tanwei
Brinker, Titus Josef
Chang-Claude, Jenny
Khader, Firas
Schuppert, Andreas
Lüdde, Tom
Trautwein, Christian
Muti, Hannah Sophie
Foersch, Sebastian
Hoffmeister, Michael
Truhn, Daniel
Kather, Jakob Nikolas
- DOI
-
10.18154/RWTH-CONV-249749
- URN
-
urn:nbn:de:101:1-2023072301324451324649
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:59 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Saldanha, Oliver Lester
- Quirke, Philip
- West, Nicholas P.
- James, Jacqueline A.
- Loughrey, Maurice B.
- Grabsch, Heike I.
- Salto-Tellez, Manuel
- Alwers, Elizabeth
- Cifci, Didem
- Ghaffari Laleh, Narmin
- Seibel, Tobias
- Gray, Richard
- Hutchins, Gordon G. A.
- Brenner, Hermann
- van Treeck, Marko
- Yuan, Tanwei
- Brinker, Titus Josef
- Chang-Claude, Jenny
- Khader, Firas
- Schuppert, Andreas
- Lüdde, Tom
- Trautwein, Christian
- Muti, Hannah Sophie
- Foersch, Sebastian
- Hoffmeister, Michael
- Truhn, Daniel
- Kather, Jakob Nikolas
- Universitätsbibliothek der RWTH Aachen
Entstanden
- 2022
Ähnliche Objekte (12)
The ecological footprint of medical AI
The ecological footprint of medical AI
Medical domain knowledge in domain-agnostic generative AI
Medical domain knowledge in domain-agnostic generative AI
Large language models and multimodal foundation models for precision oncology
Medical domain knowledge in domain-agnostic generative AI
Characterization of pathological angiogenesis in the KLEIP knockout mouse model
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis
Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images
Deep learning in cancer genomics and histopathology
A systematic analysis of deep learning in genomics and histopathology for precision oncology
Efficient reengineering of meso-scale topologies for functional networks in biomedical applications
The ecological footprint of medical AI
The ecological footprint of medical AI
Medical domain knowledge in domain-agnostic generative AI
Medical domain knowledge in domain-agnostic generative AI
Large language models and multimodal foundation models for precision oncology
Medical domain knowledge in domain-agnostic generative AI
Characterization of pathological angiogenesis in the KLEIP knockout mouse model
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis
Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images
Deep learning in cancer genomics and histopathology
A systematic analysis of deep learning in genomics and histopathology for precision oncology
Efficient reengineering of meso-scale topologies for functional networks in biomedical applications
The ecological footprint of medical AI
The ecological footprint of medical AI
Medical domain knowledge in domain-agnostic generative AI
Medical domain knowledge in domain-agnostic generative AI
Large language models and multimodal foundation models for precision oncology
Medical domain knowledge in domain-agnostic generative AI
Characterization of pathological angiogenesis in the KLEIP knockout mouse model
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis
Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images
Deep learning in cancer genomics and histopathology
A systematic analysis of deep learning in genomics and histopathology for precision oncology