AEGLE starts from real life conditions in the three medical cases i) Chronic Lymphocytic Leukemia (CLL), ii) Intensive Care Unit (ICU), and ii) Type 2 Diabetes (T2D), have been carefully chosen to cover biomedical research and questions that can set the basis for biosignal and bioinformatics analytics, multiparametric pattern mining, and integrative predictive modelling.
The development of AEGLE´s framework for Big Data analytics will allow, in the CLL case, the integration with data of different sources, the creation of advanced analytics pipelines, and refined risk stratification and the identification of novel therapeutic targets;
For the ICU the AEGLE framework will optimize mechanical ventilator and patient-ventilator interactions, improve basic patient care such as nutrition in ICU, early detection of deterioration and the development of ‘smart’ alarms;
For the T2D case, the AEGLE framework will support the definition of prognostic indicators (i.e. why some cases do better than others), it will improve methods and points for intervention, it will support the definition of accurate cohort and feasibility for clinical trial, and will improve monitoring and therapeutic modalities.