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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

M. Ranalli

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3 papers indexed here

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Open access Sep 2026

A novel model-based biclustering for ordinal data via a URV approach

We introduce a novel finite mixture model for biclustering ordinal data matrices, simultaneously clustering rows and columns within the Underlying Response Variable (URV) framework. Ordinal responses are modeled as discretizations of latent Gaussian variables, while component-specific covariance matrices are parsimonio...

M. Ranalli, F. Martella · 0 citations
Open access Oct 2026

Composite Likelihood Inference for Simultaneous Clustering and Dimensionality Reduction of Multivariate Mixed-Type Longitudinal Data

We propose a novel multivariate hidden Markov model (HMM) designed to analyze longitudinal mixed-type data comprising continuous and ordinal variables. Our model identifies and prioritizes discriminative dimensions, i.e., those useful for clustering, while separating them from noise dimensions. By modeling variables...

M. Ranalli, R. Rocci, A. Maruotti · 0 citations
Open access Jan 2026

Complications, Functional Recovery, and Quality of Life in Breast Cancer Patients Undergoing Axillary Surgery

Background Survivorship considerations have gained increasing importance in patients with early breast cancer. Every surgical procedure poses a risk of complications and a potential negative impact on patient‐reported outcomes (PROs), thereby driving growing interest in de‐escalation strategies in breast cancer surgery...

Monica Pellegrino, F. Ioppolo, M. Ranalli et al. · 0 citations

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