activity
20132026
most citedCurrent and future directions in network biology

108 citations · 155 across the 21 of their papers we have counts for

collaborators

23 papers

q-bio.OT2026

Differential Analysis of Microbial Interaction Networks

Marianna Milano, Pietro Hiram Guzzi

Microbiome studies increasingly indicate that disease-associated shifts cannot be understood from compositional changes alone. The functional architecture of microbial communities…

cs.LG2025

Kolmogorov Arnold Network Autoencoder in Medicine

Ugo Lomoio, Pierangelo Veltri, Pietro Hiram Guzzi

Deep learning neural networks architectures such Multi Layer Perceptrons (MLP) and Convolutional blocks still play a crucial role in nowadays research advancements. From a topologi…

cs.SI2025

ExDiff: A Framework for Simulating Diffusion Processes on Complex Networks with Explainable AI Integration

Annamaria Defilippo, Ugo Lomoio, Barbara Puccio +2

Understanding and controlling diffusion processes in complex networks is critical across domains ranging from epidemiology to information science. Here, we present ExDiff, an inter…

cs.CL2025

Decoding Rarity: Large Language Models in the Diagnosis of Rare Diseases

Valentina Carbonari, Pierangelo Veltri, Pietro Hiram Guzzi

Recent advances in artificial intelligence, particularly large language models LLMs, have shown promising capabilities in transforming rare disease research. This survey paper expl…

cs.LG2024

Leveraging graph neural networks for supporting Automatic Triage of Patients

Annamaria Defilippo, Pierangelo Veltri, Pietro Lio' +1

Patient triage plays a crucial role in emergency departments, ensuring timely and appropriate care based on correctly evaluating the emergency grade of patient conditions. Triage m…

cs.LG2023★ 1 cited

A novel Network Science Algorithm for Improving Triage of Patients

Pietro Hiram Guzzi, Annamaria De Filippo, Pierangelo Veltri

Patient triage plays a crucial role in healthcare, ensuring timely and appropriate care based on the urgency of patient conditions. Traditional triage methods heavily rely on human…