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CORDIS

XGlucoNet++: A Transformer-Based, Explainable and Safe Decision Support System for Personalized Glycemic Control in Intensive Care Units

Obiettivo

XGlucoNet++ aims to develop a modular, interpretable, and clinically validated AI decision support system for personalized glycemic control in Intensive Care Unit (ICU) patients. By integrating advanced transformers, reinforcement learning, and uncertainty quantification, the system will address the critical challenge of safe insulin therapy through real-time glucose forecasting and hypoglycemia risk prediction. Its hybrid architecture combines temporal deep learning, patient-specific graph representations, and evidence-aware policy learning. Aligned with Horizon Europe’s values, the project embeds ethical AI design, subgroup fairness assessments, and open science practices. Validation will be conducted on both retrospective and prospective ICU datasets, in collaboration with clinical experts, to enhance trust, transparency, and generalizability. The fellowship will accelerate the researcher’s leadership in explainable AI for health while enabling mutual knowledge exchange with the host institution.

Campo scientifico (EuroSciVoc)

Parole chiave

Programma(i)

Argomento(i)

Meccanismo di finanziamento

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Invito a presentare proposte

(si apre in una nuova finestra) HORIZON-WIDERA-2025-TALENTS-01

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Coordinatore

POLITECHNIKA SLASKA
Contributo netto dell'UE
€ 179 006,16
Indirizzo
AKADEMICKA STREET 2A
44-100 GLIWICE
Polonia
Regione
Makroregion południowy Śląskie Katowicki
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
Nessun dato