Biomedical Research Data Platform for clinical insights at scale

Scientific discoveries are harder than they look. Data scientists can spend up to 80% of their time collecting, prepping, and accessing disparate data repositories.  In biomedical research, these lengthy and time-consuming processes can negatively affect clinical study timelines, the quality of collaboration between experts, and in some cases, patient outcomes.  We’re changing that.  With Flywheel, NVIDIA, and HPE, researchers can streamline complex data management, optimize large-scale GPU processing, and safe sharing with a robust, distributed ML framework on a secure unified cloud model.  Biomedical researchers in life sciences, clinical, and academic institutions can automate data capture and improve data curation tasks from diverse, real-world sources in one place to accelerate discovery. In this webinar you hear from the foremost experts Alex Porter (HPE), Brad Genereaux (NVIDIA), and Travis Richardson (Flywheel) and how they have working together, to deliver an environment the meets three clear needs;. - Provide a readymade cloud-like data platform for AI application development and testing.    - Enable multi-centre collaboration at enterprise speed and scale in a managed environment. - Promote Data sharing to meet the need for NIH data sharing mandates securely. Speakers: Travis Richardson, Chief Strategy Officer, Flywheel Alex Porter, Global GreenLake Healthcare and Life Sciences Lead, HPE  Brad Genereaux, Global Lead Healthcare Alliances, NVIDIA