Antimicrobial resistance is one of the greatest challenges facing modern healthcare. It threatens the effective treatment of severe infections and increasingly compromises complex medical interventions, including cancer care. This project aims to improve antibiotic use, reduce the emergence of resistance, and optimize sepsis treatment through earlier and more targeted clinical decision-making.

To achieve this, the scientists are developing an intuitive dashboard that provides clinicians with relevant patient data directly at the bedside. Initially, the platform will be used for research purposes.

By leveraging artificial intelligence and large-scale hospital data, the scientists aim to predict disease trajectories more accurately and support clinical decision-making. In parallel, the scientists will develop AI-driven approaches to identify the most effective antibiotic therapy for immunocompromised patients. Ultimately, the project seeks to improve patient outcomes, reduce unnecessary antibiotic exposure, and help curb the spread of antimicrobial resistance.