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1 |
Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning models into the laboratory information system
Angeloni, Miriam. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2025
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2 |
Digital ecosystems and their impact on organizations—A dynamic capabilities approach
Volz, Felix. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2025
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3 |
Europium(iii)/terbium(iii) mixed metal–organic frameworks and their application as ratiometric thermometers with tuneable sensitivity in organic dispersion†
Joshi, Madhura. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2025
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4 |
Machine Learning Accurately Predicts Muscle Invasion of Bladder Cancer Based on Three miRNAs
Eckhart, Lea. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2025
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5 |
Stand und Perspektive von ORCID in Deutschland
Pampel, Heinz. - Berlin : Humboldt-Universität zu Berlin, 2025
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6 |
Stand und Perspektive von ORCID in Deutschland
Enthalten in Bibliothek Bd. 49, 2025, Nr. 1: 161-170. 10 S.
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7 |
Discrimination between Inflammatory and Fibrotic Activity in Crohn’s Disease-Associated Ileal-Colonic Anastomotic Strictures by Combined Ga-68-FAPI-46 and F-18-FDG-PET/CT Imaging
Enthalten in Visceral medicine Bd. 41, 2025, Nr. 1: 1-13. 12 S.
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8 |
Crystalline porous frameworks based on double extension of metal–organic and covalent organic linkages
Enthalten in Nature Synthesis 14.1.2025: 1-11
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9 |
A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing
Angeloni, Miriam. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2024
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Adapting Conductivity and Mechanical Properties through Layer Thickness Variation in Copper Niobium Laminated Metallic Composites
Kuglstatter, Moritz. - Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2024
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