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Giorgio Cazzaniga

Showing results (21-30 of 35) with videos related to

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Pathologica|January 5, 2024
Natural Language Processing to extract SNOMED-CT codes from pathological reportsGiorgio Cazzaniga, Albino Eccher, Enrico Munari, et al.
Laboratory Investigation; a Journal of Technical Methods and Pathology|August 27, 2023
Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital AnalysisGiorgio Cazzaniga, Maddalena Maria Bolognesi, Matteo Davide Stefania, et al.
Virchows Archiv : an International Journal of Pathology|March 27, 2024
Digital counting of tissue cells for molecular analysis: the QuANTUM pipelineVincenzo L'Imperio, Giorgio Cazzaniga, Mauro Mannino, et al.
Critical Reviews in Oncology/Hematology|March 10, 2026
Pathology in motion: automation from specimen to reportVincenzo L'Imperio, Angelo Paolo Dei Tos, Maurizio Carbone, et al.
Journal of Nephrology|September 28, 2023
Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directionsGiorgio Cazzaniga, Mattia Rossi, Albino Eccher, et al.
Journal of Nephrology|October 2, 2024
Galileo-an Artificial Intelligence tool for evaluating pre-implantation kidney biopsiesAlbino Eccher, Vincenzo L'Imperio, Liron Pantanowitz, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|September 6, 2024
Machine Learning Streamlines the Morphometric Characterization and Multiclass Segmentation of Nuclei in Different Follicular Thyroid Lesions: Everything in a NUTSHELLVincenzo L'Imperio, Vasco Coelho, Giorgio Cazzaniga, et al.
Kidney International Reports|August 15, 2025
Machine Learning for Monoclonal Gammopathies of Renal Significance Risk Stratification Using Clinical and Pathology DataGiorgio Cazzaniga, Giulia Capitoli, Raffaella Barretta, et al.
Endocrine Pathology|October 6, 2025
MiThyCA: A Computational Pathology Pipeline for the Identification of Microscopic Foci of Papillary Thyroid Carcinoma-Like Nuclear Features with AI in Whole-Slide Histological ImagesLeone Bacciu, Mario Urso, Vasco Coelho, et al.
Scientific Reports|January 12, 2026
Zebra bodies recognition by artificial intelligence (ZEBRA): a computational tool for Fabry nephropathyGiorgio Cazzaniga, Maurizio Carbone, Raffaella Barretta, et al.
Pageof 4

Showing results (21-30 of 35) with videos related to

Sort By:
Pageof 4
Pathologica|January 5, 2024
Natural Language Processing to extract SNOMED-CT codes from pathological reportsGiorgio Cazzaniga, Albino Eccher, Enrico Munari, et al.
Laboratory Investigation; a Journal of Technical Methods and Pathology|August 27, 2023
Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital AnalysisGiorgio Cazzaniga, Maddalena Maria Bolognesi, Matteo Davide Stefania, et al.
Virchows Archiv : an International Journal of Pathology|March 27, 2024
Digital counting of tissue cells for molecular analysis: the QuANTUM pipelineVincenzo L'Imperio, Giorgio Cazzaniga, Mauro Mannino, et al.
Critical Reviews in Oncology/Hematology|March 10, 2026
Pathology in motion: automation from specimen to reportVincenzo L'Imperio, Angelo Paolo Dei Tos, Maurizio Carbone, et al.
Journal of Nephrology|September 28, 2023
Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directionsGiorgio Cazzaniga, Mattia Rossi, Albino Eccher, et al.
Journal of Nephrology|October 2, 2024
Galileo-an Artificial Intelligence tool for evaluating pre-implantation kidney biopsiesAlbino Eccher, Vincenzo L'Imperio, Liron Pantanowitz, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|September 6, 2024
Machine Learning Streamlines the Morphometric Characterization and Multiclass Segmentation of Nuclei in Different Follicular Thyroid Lesions: Everything in a NUTSHELLVincenzo L'Imperio, Vasco Coelho, Giorgio Cazzaniga, et al.
Kidney International Reports|August 15, 2025
Machine Learning for Monoclonal Gammopathies of Renal Significance Risk Stratification Using Clinical and Pathology DataGiorgio Cazzaniga, Giulia Capitoli, Raffaella Barretta, et al.
Endocrine Pathology|October 6, 2025
MiThyCA: A Computational Pathology Pipeline for the Identification of Microscopic Foci of Papillary Thyroid Carcinoma-Like Nuclear Features with AI in Whole-Slide Histological ImagesLeone Bacciu, Mario Urso, Vasco Coelho, et al.
Scientific Reports|January 12, 2026
Zebra bodies recognition by artificial intelligence (ZEBRA): a computational tool for Fabry nephropathyGiorgio Cazzaniga, Maurizio Carbone, Raffaella Barretta, et al.
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