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Analytics to X-Rays Unchained: Adaptive AI for Healthcare at the Edge Part 2

Every stage of the human lifecycle provides a rich source of data that has the potential to enable high-performance AI solutions for Healthcare. During this two-part webinar series, we will address the importance of in situ, in silico, inference for Healthcare. In situ, AI reduces comebacks for re-imaging, accelerated triage, and decreases the timelines for diagnosis, all of which improves clinical efficiency and patient outcomes. This series will delve into a variety of AI applications from CAD and image reconstruction to NLP and AI for analytics. Finally, we will discuss the design of medical equipment and on-premises accelerators providing the necessary security, performance, flexibility, and reliability to empower clinicians with medical AI.

We are delighted to introduce guest presenters Dr. Syed Hussain and Dr Hazeem Sait of Spline.AI. Spline.AI is collaborating with Amazon Web Services and Xilinx to deliver an open-source, open-model, X-Ray classification solution for COVID-19 and Pneumonia detection.

Join us as we address the following questions:

  • From imaging to drug discovery - what are the key applications for AI in Healthcare?
  • How can we deploy adaptive AI solutions securely in-situ, in-silico, with minimal cost and maximum flexibility?
  • How can we train in the cloud and deploy in-situ? Leveraging AWS Sagemaker, TVM, PYNQ, and the Xilinx DPU to scale AI deployments
Episodes:
Analytics to X-Rays Unchained: Adaptive AI for Healthcare at the Edge Part 1
Analytics to X-Rays Unchained: Adaptive AI for Healthcare at the Edge Part 2