Synaptiq.ai

Webinar - Healthcare AI & Graph Data


Turbocharge your Healthcare Software with Graph Data and AI

The vision of personalized medicine and an efficient healthcare system relies on collecting, storing, analyzing, and applying data. Today’s healthcare system is replete with relational data stored in databases and spreadsheets and traditional business intelligence tools to generate reports and dashboards. In this fireside chat we’ll discuss how storing healthcare data in graph databases and analyzing and applying graph data using AI is the way of the future.

What you’ll learn: 

  • Why graph data is more powerful than relational data
  • How graph data and AI work together
  • Where graph data and AI apply to healthcare

Moderator & Speakers:

  Tom Blue  is a veteran and pioneer in the field direct primary care (DPC) and concierge medicine. As a builder of retainer medical practices since 2002, he has a unique perspective on the potential for medical consumerism and innovative physician practice models to accelerate the evolution of medicine in the United States.

Tom Blue is a veteran and pioneer in the field direct primary care (DPC) and concierge medicine. As a builder of retainer medical practices since 2002, he has a unique perspective on the potential for medical consumerism and innovative physician practice models to accelerate the evolution of medicine in the United States.

  Dr. Tim Oates  is Chief Data Scientist at  Synaptiq  where he leads efforts to define, prototype and build machine learning solutions for customers. He has over 25 years of experience as a researcher and practitioner in Artificial Intelligence and Machine Learning.  He's published more than 150 peer-reviewed papers on topics such as time series analysis, sequence mining, natural language processing, relational and graph mining, medical informatics, and machine vision.

Dr. Tim Oates is Chief Data Scientist at Synaptiq where he leads efforts to define, prototype and build machine learning solutions for customers. He has over 25 years of experience as a researcher and practitioner in Artificial Intelligence and Machine Learning.  He's published more than 150 peer-reviewed papers on topics such as time series analysis, sequence mining, natural language processing, relational and graph mining, medical informatics, and machine vision.

  Ryan Wright  is R&D Lead at Galois where he oversees research programs for DARPA, solving the world's most difficult problems in computer science. Over the last 15 years, he has founded three companies and led engineering teams to create practical business applications out of cutting edge research. His next startup is launching later this year aimed at improving advanced AI analytics by tailoring them to business-level problems.

Ryan Wright is R&D Lead at Galois where he oversees research programs for DARPA, solving the world's most difficult problems in computer science. Over the last 15 years, he has founded three companies and led engineering teams to create practical business applications out of cutting edge research. His next startup is launching later this year aimed at improving advanced AI analytics by tailoring them to business-level problems.

 
 

Learn more by reading our recent blog post, Applications of AI in Healthcare.