No abstract

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours.

The ODISEA platform provides Virtualized Computational Environments (VCEs) on cloud providers as the computational infrastructure to support educational activities. A VCE consists of a collection of one or more Virtual Machines (VMs) to which the students connect from their own computers. In this paper a case study is presented in the architecture domain where a PBL activity is carried out in working groups. The study involves 293 students organized in 28 pilot groups that use customized VCEs created and deployed through the ODISEA platform on a Cloud, and 30 traditional groups that use a LMS platform. The VCE provides the software, hardware and specific configuration to ease the interrelation and cooperative work between the working groups, enhancing the process tracking and feedback gathering as well as providing a better organization of the teaching material. The results demonstrate that the VCE allows to improve the cooperative work, improving the final marks in the PBL developed by the pilot working groups. Also, an economical study is presented, highlighting the economic benefits of the Cloud with respect to traditional physical laboratories of PCs.