SNIA Long Term Retention for Medical AI Applications 

In 2019, the SNIA Self-contained Information Retention Format (SIRF) became an ISO/IEC 23681:2019 standard. SIRF defines a storage container for long term retention that will enable future applications to interpret stored data regardless of the application that originally produced it. It can be beneficial in domains that need to keep data for long periods and enable search, access, and analytics on that data in the far future. The standard includes also examples of SIRF serialization on the cloud and on tapes. Radiomics is an emerging area in the medical AI community aiming to extract features from the patient multi modal medical images to improve the prediction of response to medical conditions. One challenge of radiomics is providing storage systems to efficiently store and preserve the patient medical data for future AI during the patient lifetime and beyond. The European Union H2020 BigMedilytics project includes a radiomics application that aims to predict response to breast cancer treatment.  In this talk, we’ll describe SIRF and how it can be applied in the BigMedilytics breast cancer pilot.