Author

Riccardo Cavarra

King's College London

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

Biology Disciplines

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Bioengineering· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Adelaide de VecchiiD· 1 shared Gregory Y.H. LipiD· 1 shared Magdalena KliśiD· 1 shared Oleg V. AslanidiiD· 1 shared Paolo MelidoroiD· 1 shared Samia Mostafa· 1 shared Steven Edwin WilliamsiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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1 shared paperBioengineering

Adelaide de VecchiORCID

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Author profile →

1 paper

Recent·Most cited

Comparing Machine Learning Approaches for Predicting CFD-Derived Stroke Risk Indicators in Atrial Fibrillation Patients

Paolo Melidoro, Riccardo Cavarra, Samia Mostafa, Gregory Y.H. Lip, Magdalena Kliś, Steven Edwin Williams, Oleg V. Aslanidi, Adelaide de Vecchi

This paper develops a computational fluid dynamics model of the left atrium in atrial fibrillation patients and uses machine learning to predict stroke risk indicators, finding that deep learning models achieve high accuracy.

bioRxiv · Jun 8, 2026 · PreprintBioengineering