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Peter Schüffler

Showing results (1-10 of 17) with videos related to

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Pathologie (Heidelberg, Germany)|March 13, 2024
[Artificial intelligence for pathology-how, where, and why?]Peter Schüffler, Katja Steiger, Carolin Mogler
Genes, Chromosomes & Cancer|May 31, 2023
How to use AI in pathologyPeter Schüffler, Katja Steiger, Wilko Weichert
Genome Biology|October 7, 2009
MethMarker: user-friendly design and optimization of gene-specific DNA methylation assaysPeter Schüffler, Thomas Mikeska, Andreas Waha, et al.
NPJ Precision Oncology|March 13, 2026
Multimodal fusion of pathology and radiology foundation models for WHO 2021 glioma subtypingCamillo Saueressig, Daniel Scholz, Philipp Raffler, et al.
Studies in Health Technology and Informatics|January 22, 2022
Quantifying Heterogeneity in Tumors: Proposing a New Method Utilizing Convolutional Neuronal NetworksGeorg Prokop, Michael Örtl, Marina Fotteler, et al.
Medical Image Analysis|March 27, 2026
PASS-Tr: PAtch-wise swin slice attention to leverage generalization of 2D large vision model to universal lesion detectionHan Li, Jingsong Liu, Zhen Huang, et al.
Clinical Proteomics|April 28, 2022
Use of MS-GUIDE for identification of protein biomarkers for risk stratification of patients with prostate cancerSandra Goetze, Peter Schüffler, Alcibiade Athanasiou, et al.
Orthopadie (Heidelberg, Germany)|December 19, 2025
[LLM-based extraction of clinical data: potentials and challenges]Paulina Seidl, Marton Szep, Sebastian Breden, et al.
Journal of Pathology Informatics|March 30, 2023
Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistryFrauke Wilm, Christian Ihling, Gábor Méhes, et al.
Journal of Pathology Informatics|December 21, 2020
(Re) Defining the High-Power Field for Digital PathologyDavid Kim, Liron Pantanowitz, Peter Schüffler, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Pathologie (Heidelberg, Germany)|March 13, 2024
[Artificial intelligence for pathology-how, where, and why?]Peter Schüffler, Katja Steiger, Carolin Mogler
Genes, Chromosomes & Cancer|May 31, 2023
How to use AI in pathologyPeter Schüffler, Katja Steiger, Wilko Weichert
Genome Biology|October 7, 2009
MethMarker: user-friendly design and optimization of gene-specific DNA methylation assaysPeter Schüffler, Thomas Mikeska, Andreas Waha, et al.
NPJ Precision Oncology|March 13, 2026
Multimodal fusion of pathology and radiology foundation models for WHO 2021 glioma subtypingCamillo Saueressig, Daniel Scholz, Philipp Raffler, et al.
Studies in Health Technology and Informatics|January 22, 2022
Quantifying Heterogeneity in Tumors: Proposing a New Method Utilizing Convolutional Neuronal NetworksGeorg Prokop, Michael Örtl, Marina Fotteler, et al.
Medical Image Analysis|March 27, 2026
PASS-Tr: PAtch-wise swin slice attention to leverage generalization of 2D large vision model to universal lesion detectionHan Li, Jingsong Liu, Zhen Huang, et al.
Clinical Proteomics|April 28, 2022
Use of MS-GUIDE for identification of protein biomarkers for risk stratification of patients with prostate cancerSandra Goetze, Peter Schüffler, Alcibiade Athanasiou, et al.
Orthopadie (Heidelberg, Germany)|December 19, 2025
[LLM-based extraction of clinical data: potentials and challenges]Paulina Seidl, Marton Szep, Sebastian Breden, et al.
Journal of Pathology Informatics|March 30, 2023
Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistryFrauke Wilm, Christian Ihling, Gábor Méhes, et al.
Journal of Pathology Informatics|December 21, 2020
(Re) Defining the High-Power Field for Digital PathologyDavid Kim, Liron Pantanowitz, Peter Schüffler, et al.
Pageof 2