Mayo Clinic has taken crucial steps to integrating the NVIDIA DGX SuperPod, an advanced infrastructure that provides cutting-edge AI computing capabilities, into the deployment and clinical environment of the NVIDIA DGX SuperPod and NVIDIA DGX SuperPod.
Mayo Clinic and Nvidia have worked together to contribute to Mayo Clinic's Bold and to support Mayo's platform approach to enabling rapid innovation and development of the foundational models. forward. Strategies and new innovations for generative AI solutions and digital pathology. As Mayo moves to improve patient outcomes and transform healthcare, these innovations offer new insights.
“The desire for AI is to significantly improve patient outcomes by detecting diseases quickly enough to intervene. It was once a hypothesis – “If only the right data” is becoming a reality thanks to AI and advanced computing.”
Advanced computing infrastructure initially supports the development of basic models of pathological, drug discovery and precision medicine.
Powered by Nvidia Blackwell, the DGX SuperPod is built to efficiently handle large-scale, high-resolution imaging, essential for AI Foundation model training. With a Blackwell infrastructure designed for speed and scalability, Mayo Clinic accelerates the development of pathology slide analysis and basic models, reducing the four-week task to just one, and ultimately improving patient outcomes. This advanced computing infrastructure also advances the development of Mayo Clinic's generation AI and multimodal digital pathology fundamental models.
Mayo Clinic has worked with Aignostics to develop a major pathology fundamental model called Atlas and trained full-scale images of histopathology for over 1.2 million people. With Atlas, Mayo Clinic clinicians and researchers can improve accuracy and reduce administrative tasks. New computing capabilities accelerate and improve the development of clinical models.
“This computing power, coupled with Mayo's unparalleled clinical expertise and platform data from over 20 million digitalised pathology slides, can be built on existing foundational models. We can dedicate patient care by quickly and safely developing innovative AI solutions that can improve patient outcomes and clinicians can dedicate more time to digital pathology.
/Public release, courtesy: Mayo Clinic. This material of the Organization of Origin/Author is a point-in-time nature and may be edited for clarity, style and length. Mirage.news does not take any institutional position or aspect, and all views, positions and conclusions expressed here are the views of the authors alone.
