An Introduction to Processing Unstructured Medical Data using Amazon Comprehend Medical
May 2nd, 2019 1:00PM ET
Every year, 1.2B unstructured clinical documents are created. Critical medical information is “trapped” in these documents since it’s so difficult to extract insights from them. One of the important ways to improve patient care and accelerate clinical research is by understanding and analyzing the insights and relationships that are “trapped” in free-form medical text, including hospital admission notes and a patient’s medical history. In this webinar, learn how you can use Amazon Comprehend Medical, a natural language processing service from Amazon Web Services, to process your healthcare data and gain valuable insights.
AWS HCLS Partner Tech Lead
Dr. Aaron Friedman is the Amazon Web Services (AWS) Partner Network Global Healthcare and Life Sciences technical lead. He works with independent software vendors and systems integrators to architect healthcare solutions on AWS, and bring the best possible experience to their customers. His passion is working at the intersection of science, big data, and software. Prior to working at AWS, he was the first technical employee at Human Longevity, Inc., where he built omic-guided health solutions. Aaron holds a Ph.D. in Biomedical Sciences from the University of California, San Diego and graduated summa cum laude from Washington University in St. Louis with a BS in Biomedical Engineering.
For almost 13 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 165 fully featured services from 60 Availability Zones (AZs) within 20 geographic regions. Millions of customers trust AWS to power their infrastructure, become more agile, and lower costs.
Product Lead, Amazon Comprehend Medical
Arun Ravi is the product lead for Amazon Comprehend Medical. Prior to working for AWS he was the Co-founder/CEO for Mevoked (acquired by Wellbrain) which focused on developing unique behavioral health technology. Prior to that he was the Practice Leader for Healthcare IT at Frost & Sullivan assisting various stakeholders in healthcare improve their adoption of technology. He has a Masters of Bioscience (MBS) from Keck Graduate Institute and graduated with a BS in Computer Engineering from the University of Arizona.
AWS Principal AI/Machine Learning Solutions Architect, Healthcare and Life Sciences
Ujjwal Is a Principal Machine Learning Specialist in the Global Healthcare and Lifesciences team at Amazon Web Services. He has over 13 years of experience playing different technology enabling roles in the healthcare and life sciences industry. Ujjwal has worked with large enterprises and small startups alike to design and implement solutions to solve problems involving machine learning. He has been an evangelist for AWS Healthcare AI demonstrating its use in areas like medical imaging, unstructured clinical text, precision medicine, clinical trials and quality of care improvement. His work in these areas have been featured in multiple regional and global conferences and has been published as whitepapers and blogs enjoying a wide readership.