4 Contributo in Atti di Convegno (Proceeding)

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Generative AI Techniques for Data Aggregation and Summarization: Enhancing Decision Support in Healthcare

Processing healthcare data presents significant challenges for clinicians, particularly in chronic disease management such as diabetes care. Traditional data aggregation and summarization methods often struggle to integrate the diverse data sources of health information, ranging from structured electronic health records to unstructured clinical notes. In response to this challenge, the paper proposes a reference framework that leverages generative Artificial Intelligence (AI) techniques and a...

Project “Telediabetolab”: Knowledge Gain and AI Data Process Applied in Telediabetology

The goal of the proposed paper is to provide a preliminary Artificial Intelligence (AI) approach addressing the analysis on the prevention of diabetes. The study is performed within the framework of the research project Telediabetolab and focuses on the check of the supervised Support Vector machine (SVM) algorithm to define a method to perform a data processing analysis based on predicted diabetes risk. The preliminary study highlights the possibility of defining a multi-parametric approach ...

Hybrid Systems for Post-Stroke Upper-Limb Rehabilitation: Current Trends and Future Perspectives

Hybrid systems that combine upper-limb robotics with Functional/Neuromuscular electrical stimulation (FES/NMES) aim to integrate mechanical assistance and neuromuscular activation to enhance post-stroke motor learning. A recent review on combined robot–stimulation interventions for the post-stroke upper limb reported promising outcomes, but highlighted marked heterogeneity in platforms, protocols, and outcome measures. In parallel, the Artificial Intelligence (AI)-driven rehabilitation litera...

Modeling of CNT MOSFET Transistors Enabling Self-Healing and Healing Procedures

The paper analyses the modelling of the voltage/current characterization of Carbon Nanotubes (CNTs) based n-channel MOSFET transistors. The model includes the SPICE and the Finite Element Method (FEM) simulations having the goal to highlight the damage effect on the electrical MOSFET variables and to estimate the sensitivity response of the transistor versus the electrical resistances modelling CNTs damages. The model is able to characterize the single CNT in an n-channel MOSFET layout config...

AI-Assisted Electronic Digital Twin for Liquid Level Sensors under Hardware Trojan Attack: An Experimental Validation

This work proposes an Electronic Digital Twin (EDT) circuit model for Hardware Trojan (HT) attack characterization. Specifically, the goal is to compare circuit simulations, Artificial Intelligence (AI)-based attack classification and measurements proving a liquid level sensor attack by coupling an undesired resistance between the output nodes of the sensor. The paper describes all the steps to create the AI-assisted EDT model and validates the proposed modelling approach through experimental...

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