HOSPAITAL

Publishable Summary: HospAItal envisioned transforming the way of administering inpatient care at a hospital level but primarily at the Intensive Care Unit (ICU) level. The project’s research objectives focused on using Explainable Artificial Intelligence (XAI) methods to generate robust models for the (i) early sepsis prediction up to twelve hours in advance, (ii) ICU length of stay prediction, (iii) Hospitalization prediction following Emergency Department (ED) triage, (iv) ED critical outcome (i.e., death of ICU admission) prediction, (v) ED length of stay prediction.

Key to the project success lied in the development of a robust, interoperable software infrastructure, that can acquire, interlink and deliver the entirety of the available clinical data for data analysis purposes, while facilitating interactive visualisation dashboards under a single Electronic Health Record (EHR) system. Overall, the goal was to integrate and automate core hospital resources and processes, for the medical experts to make informed and timely decisions, harnessing the wealth of clinical data and AI-based predictive models, for the benefit of the citizen/ patient.

Duration: 02/2023- 04/2025

Please visit the HospAItal project website for more information: https://hospitalai.eu/

The project Hospital Transformation through Artificial Intelligence – HOSPAITAL, CODEVELOP-ICT-HEALTH/0322/0071 is funded by the European Union Recovery and Resilience Facility of the NextGenerationEU instrument, through the Research and Innovation Foundation