P. H. Guzzi

FibrilNet maps conserved and tissue-specific molecular environments across systemic amyloidoses

Deep Learning-Based Malaria Parasite Image Classification on Real Microscopy Data

The findings demonstrate that convolutional, transformer-based, and hybrid deep learning architectures can be successfully trained on real microscopy data for species-level malaria diagnosis and support the feasibility of deploying scalable, automated diagnostic systems to improve both accuracy and accessibility of mal...

Comparing Mpox epidemic controls through simulations and explainable graph convolution networks: A case study in the Republic of the Congo and Nigeria

The study supports the potential usefulness of combining contact-based models with explainable graph neural networks for scenario-based epidemic analysis and suggests that the k-GCN model captures relevant temporal and structural dependencies in the simulated graph-organized data.

Cross-domain integration of transcriptomic modalities through graph neural networks