Author

Pietro Lio'

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Open access Oct 2026

AGraphHF: Adversarial graph-based multimodal learning for heart failure risk prediction.

Heart failure (HF) is a major cause of morbidity, mortality, and healthcare utilization worldwide, yet early risk stratification remains challenging because prognostic information is distributed across heterogeneous clinical narratives and subtle electrophysiological abnormalities. We propose AGraphHF, a multimodal fra...

Tadiyos Hailemichael Mamo, M. Hasanuzzaman, Haibo Wang et al. · Artificial Intelligence in M... · 0 citations

#artificial intelligence Open access Sep 2026

AutoHGNN: Robust and efficient neural architecture search for hypergraph neural networks

This paper proposes AutoHGNN, a neural architecture search framework tailored for hypergraph neural networks, and introduces a Hyper-Interaction Module (HIM) into the search space to address the mismatch between conventional graph neural network designs and hypergraph data.

Sirui Li, Pietro Lio', Xin-Sheng Li et al. · Knowledge-Based Systems · 0 citations

Open access Aug 2026

De novo design of RNA pseudoknots with deep learning.

It is shown that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures, suggesting that some difficult RNA design tasks may be tractable without first solving RNA 3D structure prediction.

J. Townley, W. Kladwang, David Baker et al. · Science · 1 citation