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Toward Explainable Artificial Intelligence for Precision Pathology.
Klauschen, Frederick; Dippel, Jonas; Keyl, Philipp; Jurmeister, Philipp; Bockmayr, Michael; Mock, Andreas; Buchstab, Oliver; Alber, Maximilian; Ruff, Lukas; Montavon, Grégoire; Müller, Klaus-Robert.
Affiliation
  • Klauschen F; Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany; email: f.klauschen@lmu.de.
  • Dippel J; Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany.
  • Keyl P; Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany.
  • Jurmeister P; German Cancer Consortium, German Cancer Research Center (DKTK/DKFZ), Munich Partner Site, Munich, Germany.
  • Bockmayr M; Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany.
  • Mock A; Machine Learning Group, Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany; email: klaus-robert.mueller@tu-berlin.de.
  • Buchstab O; Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany; email: f.klauschen@lmu.de.
  • Alber M; Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany; email: f.klauschen@lmu.de.
  • Ruff L; German Cancer Consortium, German Cancer Research Center (DKTK/DKFZ), Munich Partner Site, Munich, Germany.
  • Montavon G; Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany.
  • Müller KR; Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Annu Rev Pathol ; 19: 541-570, 2024 Jan 24.
Article in En | MEDLINE | ID: mdl-37871132
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Precision Medicine Limits: Humans Language: En Journal: Annu Rev Pathol Journal subject: PATOLOGIA Year: 2024 Document type: Article
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Precision Medicine Limits: Humans Language: En Journal: Annu Rev Pathol Journal subject: PATOLOGIA Year: 2024 Document type: Article