Healthcare is one of the key sectors of global economy, particularly in Europe, where it accounts for 9% of the average GDP. The health sector benefits, directly or indirectly, from most scientific and technological advances, including those originally developed for other non-health related sectors. The use of technology in health is clearly a major driver towards more efficient healthcare, from whom both people and national health service budgets can benefit. European national healthcare systems are generating large biomedical imaging datasets because many medical examinations use image-based processes; these datasets are growing and constitute a large database of knowledge because most of their value derives from expert interpretations of those images. To promote eHealth innovation and improvement in Europe, the Rad4AI project, the Italian branch of the European DeepHealth project, promotes the development of standardized software to manipulate and process images in a more efficient way, thus increasing the productivity of professionals working on biomedical images. Using the HPC4AI resources of the Piedmont Region (high performance computers), Rad4AI addresses the e-Health challenge by proposing a hybrid HPC + Big Data solution to efficiently support state-of-the-art Deep Learning algorithms to improve European medical software platforms.
The Deep-Learning and HPC to Boost Biomedical Applications for Health (DeepHealth) project is funded by the EC under the ICT-11-2018-2019 action “HPC and Big Data enabled Large-scale Test-beds and Applications”. DeepHealth is a 3 years project, which began in mid-January 2019 and will conclude in June 2022. The goal of DeepHealth is to provide a unified framework to take advantage of underlying heterogeneous HPC and Big Data architectures and to implement state-of-the-art techniques in Deep Learning and Computer Vision. In particular, the project combines High-Performance Computing (HPC) infrastructures with Deep Learning (DL) and Artificial Intelligence (AI) techniques to support biomedical applications that require the analysis of large and complex biomedical datasets and, thus, new and more efficient ways of diagnosing, monitoring and treating diseases.
The project includes dissemination events, “Deephealth Piedmont Branch-the clinical experience” will take stock, with the European partnership, of knowledge acquired during last 3 years.

Language: English
Proposed audience: clinical
Fee and registration information: Participation is free of charge but registration is required though https://www.medtorino.unito.it/eventiecm/?event=deephealth-piedmont-branch-the-clinical-experience-webinar.
Certificate and CME credits:
Participation certificate and CME credits are provided to the attendees at the following conditions:
– take part in the total event (90% hours)
– fill in the documents that will be provided at the event
– pass the final learning test (ECM assessment questionnaire) with minimal 75% score
International attendees can get the credits from the Italian official provider (University of Torino) and then request their national institutions to convert/recognise the validity of the credits in their own country.