Healthcare companies are collecting massive amounts of data, growing at exponential rates to fuel important advances in the industry through the use of AI. These same companies stand as stewards of some of the most sensitive data today: patient outcomes, claims data, genomic information, and more. The business imperatives to leverage this data for better patient outcomes, network optimization and lower costs are clear. But how do business and analytics leaders in healthcare deal with the competing need to maintain the privacy of their data sets?
- Explore what it means to “maintain privacy”
- Learn the shortcomings of traditional approaches to protect privacy
- Understand Differential Privacy: a new, mathematically rigorous approach to privacy
- Review the impact on business and patient outcomes
VP of Marketing, LeapYear Technologies
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Sponsored by LeapYear Technologies, a HIMSS20 Artificial Intelligence / Machine Learning Circle Sponsor