BC-ISCEP: Better Care Intelligent System to Prevent Critical Events

Project aimed at the development of an intelligent system based on clinical data for the early detection of critical events in ICU patients. It integrates physiological signals and ventilatory parameters using advanced algorithms that allow us to identify patterns of clinical deterioration. Its approach improves continuous monitoring, optimizes patient-ventilator interaction and contributes to more proactive care, reducing complications and improving care efficiency in intensive care environments.

Develop an automated system that allows the early detection of clinical risk situations in critical patients through continuous data analysis. The project seeks to optimize ventilatory synchrony, reduce the need for sedation and improve clinical outcomes. In addition, it aims to facilitate decision-making through tools based on artificial intelligence that provide relevant and actionable information for healthcare professionals.

• Creation of integrated predictive algorithms to anticipate adverse events and prevent clinical deterioration.
• Integration of multiple physiological signals into a single clinical decision support platform.
• Deployment of automated tools to optimize rapid medical response in critical environments.