Predictive Risk Identification of Sepsis with Machine learning – PRISM
Partners
Università Campus Bio-Medico di Roma
PI: Prof. Letizia Chiodo
people: Prof. Simonetta Filippi, Dr. Alessandro Loppini, Prof. Silvia Angeletti.
Università di Salerno
local PI: Adolfo Santoro
people: Agostino Aiezzo, Mario Vigliar, Prisco Trotta
Nelke S.r.l.
local PI: Mario Garofano
Funded by the Italian National Recovery and Resilience Plan (NRRP), M4C2, European Union –NextGenerationEU, through the Research Program “National Centre for HPC, Big Data and Quantum Computing”, Project CN00000013, Spoke 6, CUP B83C22002940006 (Cascade Funding Spoke 6).
National Centre for HPC, Big Data and Quantum Computing, Spoke 6
We presented our results at the 20th Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2025 held in Milan, Italy, with a poster contribution titled “Predictive Risk Identification of Sepsis with Machine Learning”.
We presented our results at the 20th Bioinformatics and Computational Biology Conference, BBCC 2025, held in Naples, Italy, with an oral contribution titled “Early Sepsis Prediction using Time-Series Machine Learning: A Multi-Dataset Analysis and Dynamic Risk Stratification”.
The tool PRISM is available here.
The developed ML models are available here.