Healthcare AI

114 Pages·2017·13.9 MB·English

by  Dreyer, Keith J.

Healthcare AI
Radiology’s Next Frontier
Dr. Keith Dreyer
Chief Data Science Officer, MGH, BWH, Partners Healthcare
Associate Professor of Radiology, Harvard Medical School
Chief Science Officer, American College of Radiology Data Science Institute
ACR Board of Chancellors, Chairman Informatics Commission
Our Role as Physicians
1 Prevent illness
2 Help sick patients get healthy as soon as possible
3 Stabilize & manage patients with chronic conditions
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Healthcare Spending as a Percentage of GDP (1995-2014)
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Institute of Medicine: Improving Diagnosis In Health Care
1999 2015
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Radiologist Relevance In Error Reduction
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The US Healthcare System’s Response: The Quadruple Aims
Improving the health Improving the individual
of populations experience of care
Reducing the per capita
Improving the work life of
costs of care
those who deliver care
Doing Better With Less…
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Data Science and Artificial Intelligence: A Rapidly Emerging Megatrend in Business and Society
Hype?
Reality?
Yes. Yes.
© 2017 | DATA SCIENCE INSTITUTE™: AMERICAN COLLEGE OF RADIOLOGY | ALL RIGHTS RESERVED.
Convergence of rapid advances and growth on multiple fronts:
1. Storage and processing power as a cheap, on-demand utility:
– Graphics Processing Units (GPUs)
– Cloud computing allows affordable GPUs at scale
2. Exponential growth in data to analyze using AI in many fields.
In healthcare:
– Medical Imaging
– Electronic health records
– Genomic data
What’s fueled the – Patient monitoring and treatment devices (e.g., EKG, Pulse,
Oxygen, IV Pumps, etc..)
growth in AI applications
– Consumer biomonitoring devices (e.g., Fitbit, Apple Watch,
smartphones)
in the last 5 years?
– High resolution imaging devices
– Data registries
– Environmental data
– Evidence-based guidelines
– Clinical trial and other research data
– Medical literature and supporting primary data
© 2017 | DATA SCIENCE INSTITUTE™: AMERICAN COLLEGE OF RADIOLOGY | ALL RIGHTS RESERVED.
These technological advances and data growth have spurred:
1. Powerful new applications for known AI techniques
(e.g., deep learning)
2. A global, online community of AI practitioners sharing
advances daily
3. Open source software from the community and tech
What’s fueled the
giants (e.g. Nvidia’s DIGITS, Google’s TensorFlow,
Amazon/Microsoft’s Gluon)
growth in AI applications
in the last 5 years?
4. Huge AI investments from tech titans who see AI as a
strategic asset
© 2017 | DATA SCIENCE INSTITUTE™: AMERICAN COLLEGE OF RADIOLOGY | ALL RIGHTS RESERVED.
Definition of Data Science
“”
• Data Science is an interdisciplinary field that allows its practitioners to
understand and analyze actual phenomena with data.
• “Interdisciplinary” means that data scientists are trained in three
complementary but distinct areas:
1. Mathematics and Statistics
2. Computer science & the sub-fields of artificial intelligence and
machine learning
3. Subject matter knowledge about the analysis topic (i.e., How that
domain’s “facts” are represented in the data)
“”
© 2017 | DATA SCIENCE INSTITUTE™: AMERICAN COLLEGE OF RADIOLOGY | ALL RIGHTS RESERVED.