Author

Tobias Seibel

Universitätsklinikum AachenORCID 0009-0004-9115-3228Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Approach:statistical model· 1

Frequent Co-Authors

Didem ÇifçiiD· 2 shared Hannah Sophie MutiiD· 2 shared Jakob Nikolas KatheriD· 2 shared Marko van TreeckiD· 2 shared Alexandra F. LearyiD· 1 shared Andreas SchuppertiD· 1 shared Chiara Maria Lavinia LoeffleriD· 1 shared Christian TrautweiniD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Didem ÇifçiORCID

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2 papers

Recent·Most cited

Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study

Chiara Maria Lavinia Loeffler, Omar S. M. El Nahhas, Hannah Sophie Muti, Tobias Seibel, Didem Çifçi, Marko van Treeck, Marco Gustav, Zunamys Itzell Carrero, Nadine Therese Gaisa, Kjong-Van Lehmann, Alexandra F. Leary, Pier Selenica, Jorge Sergio Reis-Filho, Nadina Ortiz Bruechle, Jakob Nikolas Kather

This study uses attention-based multiple instance learning to predict HRD status from H&E images across ten tumor types, achieving moderate to high AUROC values.

medRxiv · Mar 8, 2023 · PreprintGenetic & Genomic Medicine

Swarm learning for decentralized artificial intelligence in cancer histopathology

Oliver Lester Saldanha, Philip Quirke, Nicholas Paul West, Jacqueline A. James, Maurice Bernard Loughrey, Heike Irmgard Grabsch, Manuel Salto‐Tellez, Elizabeth Alwers, Didem Çifçi, Narmin Ghaffari Laleh, Tobias Seibel, Richard G. Gray, Gordon G. A. Hutchins, Hermann Brenner, Marko van Treeck, , Jakob Nikolas Kather

This paper demonstrates swarm learning for training AI models on decentralized histopathology data to predict molecular features in colorectal cancer.

Nature Medicine · Apr 25, 2022Peer-reviewedBioinformatics