Author

Davide Rizzi

GPI SpA (Italy)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Genetic & Genomic Medicine· 1 Pathology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Arndt HartmanniD· 2 shared Fulvia FerrazziiD· 2 shared Miriam AngeloniiD· 2 shared Alessandro CaputoiD· 1 shared Annett HölskeniD· 1 shared Christoph SchubartiD· 1 shared Filippo Fraggetta· 1 shared Filippo FraggettaiD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersGenetic & Genomic Medicine

Arndt HartmannORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

A fully-automated integrative workflow to streamline NGS-based analyses within Molecular Tumour Boards

Maria Giulia Carta, Miriam Angeloni, Lars Tögel, Christoph Schubart, Annett Hölsken, Robert Stoehr, Simona Vatrano, Davide Rizzi, Paolo Magni, Filippo Fraggetta, Arndt Hartmann, Florian Haller, Fulvia Ferrazzi

This paper develops a fully-automated workflow to streamline NGS-based analyses in Molecular Tumour Boards by integrating variant interpretation and biomarker estimation.

medRxiv · Dec 15, 2025 · PreprintGenetic & Genomic Medicine

Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning algorithms into the laboratory information system

Miriam Angeloni, Davide Rizzi, Simon Schoen, Alessandro Caputo, Francesco Merolla, Arndt Hartmann, Fulvia Ferrazzi, Filippo Fraggetta

This paper presents a framework for integrating deep-learning models into the laboratory information system using open-source tools and HL7 standards to support clinical adoption in digital pathology.

Genome Medicine · May 26, 2025Peer-reviewedPathology