Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types.
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| Title: | Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types. |
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| Authors: | Loeffler CML; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany.; Department of Medicine I, Faculty of Medicine Carl Gustav Carus, University Hospitaland, Technische Universität Dresden , Dresden, Germany., El Nahhas OSM; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany., Muti HS; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany.; Department for Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany., Carrero ZI; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany., Seibel T; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany., van Treeck M; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany., Cifci D; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany., Gustav M; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany., Bretz K; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany., Gaisa NT; Institute of Pathology, University Hospital RWTH Aachen, Aachen, Germany.; Joint Research Center Computational Biomedicine, University Hospital RWTH Aachen, Aachen, Germany., Lehmann KV; Institute of Pathology, University Hospital RWTH Aachen, Aachen, Germany.; Joint Research Center Computational Biomedicine, University Hospital RWTH Aachen, Aachen, Germany.; Center for Integrated Oncology, Aachen Bonn Cologne Duesseldorf (CIO ABCD), Duesseldorf, Germany.; Cancer Research Center Cologne-Essen, University Hospital Cologne, Cologne, Germany., Leary A; Gynecological Cancer Unit, Department of Medicine, Institut Gustave Roussy, Villejuif, France., Selenica P; Experimental Pathology, Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Reis-Filho JS; Experimental Pathology, Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Ortiz-Bruechle N; Institute of Pathology, University Hospital RWTH Aachen, Aachen, Germany.; Center for Integrated Oncology, Aachen Bonn Cologne Duesseldorf (CIO ABCD), Duesseldorf, Germany., Kather JN; Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany. jakob-nikolas.kather@alumni.dkfz.de.; Department of Medicine I, Faculty of Medicine Carl Gustav Carus, University Hospitaland, Technische Universität Dresden , Dresden, Germany. jakob-nikolas.kather@alumni.dkfz.de.; Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. jakob-nikolas.kather@alumni.dkfz.de.; Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany. jakob-nikolas.kather@alumni.dkfz.de. |
| Source: | BMC biology [BMC Biol] 2024 Oct 08; Vol. 22 (1), pp. 225. Date of Electronic Publication: 2024 Oct 08. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101190720 Publication Model: Electronic Cited Medium: Internet ISSN: 1741-7007 (Electronic) Linking ISSN: 17417007 NLM ISO Abbreviation: BMC Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1741-7007 |
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| DOI: | 10.1186/s12915-024-02022-9 |
