New Advances in Generative AI & Machine Learning for Healthcare

Thousands of healthcare customers work with Amazon Web Services (AWS) today, from healthcare providers to payors to government healthcare organizations at all levels of government, healthcare IT vendors, research organizations. Across this spectrum, we are working on a wide range of use cases, enabling organizations to use data in new ways, improve engagement and experience, and provide new insights. We’re helping providers improve the quality of care and efficiency, and reduce costs. One significant trend has been an acceleration in the application of machine learning (ML) in healthcare. At AWS, we’ve played a key role in democratizing ML and artificial intelligence (AI), and making it accessible to anyone who wants to use it, including more than 100,000 customers of all sizes and industries. This includes new tools to easily build and scale generative AI applications with foundation models (FMs). During this presentation, dive into the AWS generative AI portfolio and key healthcare use cases, as well as the most important factors enabling customers to quickly build and deploy generative AI applications at scale. Check out a demonstration on augmenting intelligent document processing workflows with generative AI, which could be applied in a variety of healthcare use cases including summarization of patient charts, clinical consultations or clinician/patient Q&A. Fred S Azar, PhD is responsible for Artificial Intelligence & Machine Learning Business Development in healthcare at Amazon Web Services. He has 20+ years of industry experience in healthcare technology innovation and previously held leadership positions at IBM Watson Health, Philips, Siemens & InterSystems. Veda Raman is a Senior Solutions Architect for AI and ML based in Maryland. Veda works with customers to help them architect efficient, secure and scalable AI and ML applications.