| Project number | SNN01 |
| Category | Basic Research |
| Field of science | Not specified |
| Universities involved | Universität Graz, Universidad de Granada |
| Project duration | April 1, 2026 - January 12, 2027 |
| Status | In progress |
| Project leader | ROCIO CELESTE ROMERO ZALIZ |
| Participants | Arianna Crocetti , Agnieszka Łętowska |
| Available positions | 2 |
| Project URL | https://produccioncientifica.ugr.es/investigadores/357293/detalle |
| Data coordinator | ROCIO CELESTE ROMERO ZALIZ |
| Keywords | SNN, AI, Engeneering |
| Short description | This research project explores the application of Spiking Neural Networks (SNNs) to predict and optimize clinical outcomes for virtual ICU patients. By leveraging biologically inspired neural dynamics, SNNs enable real-time processing of temporal data streams such as vital signs and lab results, offering a more efficient and interpretable alternative to traditional deep learning models. The project simulates critical care scenarios using virtual patient datasets to evaluate SNN-based decision support systems for tasks like early detection of sepsis, adaptive ventilator settings, and personalized treatment strategies. The ultimate goal is to enhance predictive accuracy and computational efficiency in ICU environments while maintaining clinical interpretability. |