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Stefano Marchesin

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

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BMC Bioinformatics|April 1, 2022
TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation ExtractionStefano Marchesin, Gianmaria Silvello
BMC Bioinformatics|March 15, 2024
MetaTron: advancing biomedical annotation empowering relation annotation and collaborationOrnella Irrera, Stefano Marchesin, Gianmaria Silvello
Database : the Journal of Biological Databases and Curation|September 28, 2023
Building a large gene expression-cancer knowledge base with limited human annotationsStefano Marchesin, Laura Menotti, Fabio Giachelle, et al.
Journal of Biomedical Semantics|August 29, 2024
An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser OntologyGuglielmo Faggioli, Laura Menotti, Stefano Marchesin, et al.
Medical Image Analysis|August 18, 2024
Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learningNiccolò Marini, Stefano Marchesin, Marek Wodzinski, et al.
Journal of Pathology Informatics|September 14, 2023
Modelling digital health data: The ExaMode ontology for computational pathologyLaura Menotti, Gianmaria Silvello, Manfredo Atzori, et al.
Journal of Pathology Informatics|October 21, 2022
Empowering digital pathology applications through explainable knowledge extraction toolsStefano Marchesin, Fabio Giachelle, Niccolò Marini, et al.
Journal of Pathology Informatics|September 2, 2025
Automatic labels are as effective as manual labels in digital pathology images classification with deep learningNiccolo Marini, Stefano Marchesin, Lluis Borras Ferris, et al.
NPJ Digital Medicine|July 22, 2022
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotationsNiccolò Marini, Stefano Marchesin, Sebastian Otálora, et al.
Scientific Data|November 21, 2025
The BRAINTEASER Datasets: Clinical, Wearable and Environmental Data for ALS & MS Progression ModelingGuglielmo Faggioli, Laura Menotti, Stefano Marchesin, et al.
Pageof 1

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

Sort By:
Pageof 1
BMC Bioinformatics|April 1, 2022
TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation ExtractionStefano Marchesin, Gianmaria Silvello
BMC Bioinformatics|March 15, 2024
MetaTron: advancing biomedical annotation empowering relation annotation and collaborationOrnella Irrera, Stefano Marchesin, Gianmaria Silvello
Database : the Journal of Biological Databases and Curation|September 28, 2023
Building a large gene expression-cancer knowledge base with limited human annotationsStefano Marchesin, Laura Menotti, Fabio Giachelle, et al.
Journal of Biomedical Semantics|August 29, 2024
An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser OntologyGuglielmo Faggioli, Laura Menotti, Stefano Marchesin, et al.
Medical Image Analysis|August 18, 2024
Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learningNiccolò Marini, Stefano Marchesin, Marek Wodzinski, et al.
Journal of Pathology Informatics|September 14, 2023
Modelling digital health data: The ExaMode ontology for computational pathologyLaura Menotti, Gianmaria Silvello, Manfredo Atzori, et al.
Journal of Pathology Informatics|October 21, 2022
Empowering digital pathology applications through explainable knowledge extraction toolsStefano Marchesin, Fabio Giachelle, Niccolò Marini, et al.
Journal of Pathology Informatics|September 2, 2025
Automatic labels are as effective as manual labels in digital pathology images classification with deep learningNiccolo Marini, Stefano Marchesin, Lluis Borras Ferris, et al.
NPJ Digital Medicine|July 22, 2022
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotationsNiccolò Marini, Stefano Marchesin, Sebastian Otálora, et al.
Scientific Data|November 21, 2025
The BRAINTEASER Datasets: Clinical, Wearable and Environmental Data for ALS & MS Progression ModelingGuglielmo Faggioli, Laura Menotti, Stefano Marchesin, et al.
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