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Not surprisingly the reality and opportunities with artificial intelligence are both more interesting and more complex…. This report wonderfully unwraps these often disempowering descriptions and provides the reader with simple clarity about what data is needed and how to think about the tools to analyze that data.
Don Rucker M.D., National Coordinator for Health Information Technology

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Section 1: WHAT IS AI AND HOW CAN IT BE USED IN HEALTHCARE?
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Today, “artificial intelligence” can be a term difficult to define. Section 1 walks through the “anatomy” of a machine learning algorithm and dives into easy-to-understand example models.

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This section also showcases different health AI capabilities and demonstrates how AI might be applied in the patient journey of a person with diabetes.

Section 2: WHAT IS NECESSARY TO SUCCESSFULLY CREATE AND ADOPT A HEALTH AI SOLUTION?

Section 2 explores market dynamics and commercialization considerations for health AI applications, from ideation, piloting, and adoption.

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Penn Medicine’s Predictive Healthcare team provides insight to how leading providers are thinking about and applying AI in a clinical setting.

Section 3: CASE STUDIES OF AI APPLICATIONS IN HEALTHCARE

HAIN interviewed founders and executives at 3 different successful health AI startups to learn about their development process and lessons learned.  

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Interview with: Andrew Le MD, co-founder & CEO        
Buoy is an A.I. health assistant that chats with patients to better understand symptoms and identify what’s wrong

Interview with: Jason Bhan MD, co-founder & CMO
​Prognos aggregates, normalizes, and provides clinical interpretation of clinical diagnostics data at scale, using HIPAA compliant infrastructure

Interview with: Eyal Gura, co-founder & CEO
​Zebra Medical Vision is a  Medical imaging insights platform (“Radiology Assistant”) that supports radiologists with automated, accurate, and timely imaging diagnostics.

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