September 26-27, 2016
New York, NY

Achieving precision medicine at scale: Building medical AI to predict individual disease evolution in real time

Ash Damle (Lumiata)
3:45pm–4:25pm Tuesday, 09/27/2016
Verticals and applications
Location: 3D09 Level: Beginner

Prerequisite knowledge

  • A basic understanding of machine learning
  • General knowledge of graphs and deep learning
  • What you'll learn

  • Learn the complexities that come with managing health data
  • Understand a real-world example of how to build and apply AI in healthcare
  • See how the right application of graph models, NLP, and deep learning applications can address key challenges in healthcare today
  • Description

    Improving delivery of healthcare rests on the ability to predict individual disease with precision, accuracy, and speed. Healthcare’s progress rests on two core capabilities: the first is identifying an individual’s current and future health state; the second is determining the subsequent best course of action per individual. Both need to be done with precision and timeliness to enable real-time action and iteration with data. This demands the ability to combine, organize, normalize, interpret, and take action on highly complex structured and unstructured data at speed and scale. And yet, most organizations lack the skills and manpower to do so, leading to labor-intensive and costly processes.

    AI holds tremendous potential to fill this gap, but the industry has not yet grasped the right approaches required to make an impact. How can AI address the growing complexity and volume, speed, and variance of health data? We need models that understand the context and meaning of health data and that can compute against it. Ash Damle explores the key data and analytics roadblocks that healthcare actors face and sheds light on practical applications of AI within the workflows of health plans and hospitals. Ash explains how Lumiata’s Medical AI automatically unifies multisourced health data and applies graph models, NLP, and deep learning to deliver medically relevant analytics to surface the signal from the noise and predict disease with high precision in real time.

    Photo of Ash Damle

    Ash Damle

    Lumiata

    As the founder and CEO of Lumiata, Ash Damle drives the company’s vision of leveraging the best of data science and medical knowledge to power high-value healthcare around the world. At Lumiata, Ash has pioneered the Lumiata Medical Graph, a first-of-its-kind medical graph based on current scientific research and clinical practice that combines multisourced health data with medical knowledge and analyzes the complex, multidimensional relationships between them, allowing for the delivery of hyperpersonalized business and clinical insights across the entire healthcare network. Ash is a technologist and data scientist deeply rooted in the application of big data to health and its intersection with design as well as a global entrepreneur, who has worked with clients and partners in the United States, China, the UK, Canada, Australia, France, Germany, India, and Japan. He graduated from MIT with degrees in both computer science and mathematics, has published numerous papers, and has received patents in real-time unstructured semantic analysis.