SUMMARY REMARKS & TESTBEDS
The med.iwelli.com platform enables doctors to store heterogeneous data (vital signs from their patients, documents, pictures like MRI, photos of medical exams, document file types such as pdf, textual content like the medical history of the patient, financial records, audio files and many others). It is more than an Electronic Health Record (EHR) since it allows for more complex data to be captured and stored. Within the realm of our strategy one of our goals is to get value out of the heterogeneous content we store in the med.iwelli.com platform digitising and analysing all images and documents stored in the platform using machine learning capabilities. We believe that Tengu as a platform for big data experimentation will allow us to store and analyse our heterogeneous data at an affordable cost. We wish to experiment with Tengu to store multimedia content (such as MRI images, video and audio files, documents), create a fully automated service (scripts) for offline and real-time data analysis of the content and allow this content to be transferred among different nodes (servers, platforms, end-users). The use case concerns image recognition and OCR analysis and metadata labelling of the document files stored in Tengu and cooperation between different actors (nodes).