Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

This study establishes that HRD can be directly predicted from H&E slides using attMIL, demonstrating its applicability across nine different tumor types.

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Publication Details

Journal
BMC Biology
Published
2024-10-08
DOI
https://doi.org/10.1186/s12915-024-02022-9
Citations
13
Primary Topic
PARP inhibition in cancer therapy
Type
article
Field-Weighted Citation Impact
3.39

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article

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Hannah Sophie Muti, Tobias Seibel, Pier Selenica, Kjong-Van Lehmann et al.
13 citations
BMC Biology
PARP inhibition in cancer therapy
3.39
article

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Hannah Sophie Muti, Tobias Seibel, Pier Selenica, Kjong-Van Lehmann, Alexandra Léary, Marko van Treeck, Marco Gustav, Didem Çifçi, Zunamys I. Carrero, Jakob Nikolas Kather, Omar S. M. El Nahhas, Nadine Therese Gaisa, Jorge S. Reis‐Filho, Chiara Maria Lavinia Loeffler, Kevin Bretz, Nadina Ortiz-Bruechle
article en
13 citations

Abstract

This study establishes that HRD can be directly predicted from H&E slides using attMIL, demonstrating its applicability across nine different tumor types.

BMC BiologyVol. 22(1)
University of Leeds (GB), Memorial Sloan Kettering Cancer Center (US), Heidelberg University (DE), St James's University Hospital (GB), Institut Gustave Roussy (FR), University Hospital Heidelberg (DE), Integrated Oncology (United States) (US), National Center for Tumor Diseases (DE), University Hospital Cologne (DE), University Hospital Carl Gustav Carus (DE), RWTH Aachen University (DE)
National Institute for Health and Care Research, Department of Health and Social Care, European Commission, Deutscher Akademischer Austauschdienst, Bundesministerium für Bildung und Forschung, Technische Universität Dresden, Bundesministerium für Gesundheit, Deutsche Krebshilfe, Gemeinsame Bundesausschuss, Leeds Biomedical Research Centre
Good health and well-being
Openalex Percentile: Top 6%
PARP inhibition in cancer therapy
3.39
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