Do explainable AI (XAI) methods improve the acceptance of AI in clinical practice? An evaluation of XAI methods on Gleason grading.
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| Title: | Do explainable AI (XAI) methods improve the acceptance of AI in clinical practice? An evaluation of XAI methods on Gleason grading. |
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| Authors: | Manz R; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Bäcker J; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Cramer S; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Meyer P; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Müller D; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany.; IT-Infrastructure for Translational Medical Research, University of Augsburg, Augsburg, Germany., Muzalyova A; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Rentschler L; Institute for Pathology and Molecular Diagnostics, University Hospital of Augsburg, Augsburg, Germany., Wengenmayr C; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Hinske LC; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany., Huss R; Institute for Pathology and Molecular Diagnostics, University Hospital of Augsburg, Augsburg, Germany.; BioM Biotech Cluster Development GmbH, Planegg, Germany., Raffler J; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany.; Bavarian Cancer Research Center (BZKF), Augsburg, Germany., Soto-Rey I; Digital Medicine, University Hospital of Augsburg, Augsburg, Germany. |
| Source: | The journal of pathology. Clinical research [J Pathol Clin Res] 2025 Mar; Vol. 11 (2), pp. e70023. |
| Publication Type: | Journal Article; Evaluation Study; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Wiley Blackwell Country of Publication: England NLM ID: 101658534 Publication Model: Print Cited Medium: Internet ISSN: 2056-4538 (Electronic) Linking ISSN: 20564538 NLM ISO Abbreviation: J Pathol Clin Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2056-4538 |
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| DOI: | 10.1002/2056-4538.70023 |
