Leader: Rocco Oliveto (UNIMOL); Other collaborator(s): UNIMOL
This task will establish an appropriate e-health platform and design an advanced decision support system to support the medical staff in the identification of abnormalities in older adults and to craft an admissions risk index after the hospitalization for heart and respiratory failure. The abnormalities will focus on the cardiovascular and the respiratory systems, and functional and cognitive impairment. Explainable machine learning techniques will be used for data analysis. This will alert the medical staff on specific anomaly and will highlight factors that led to its identification. Furthermore, based on the concept of continuous learning, the system will learn from operator’s feedback with the aim of improving its accuracy.
Brief description of the activities and of the intermediate results
Following tight collaboration between the multidisciplinary team and the task#2 leader's team, the e-health patients management platform is currently underway at the last stage of realization and is expected to be ready for monitoring devices coupling and testing by july.
As anticipated in previous report, the e-health patients management platform is ready for coupling with monitoring devices.
The e-health based patients and aregiver management platform has almost been completed and coupled with the available wearable monitoring devices. Although not completed, the platform's core functions have been showed in the meeting held in Termoli (CB) on the 12 of september.