Access to data is crucial for the development of AI. Yet before safely sharing data, physicians face challenges, including defining who owns it, determining its value and evaluating whether it should be shared. In this video series, we’ll explore the top considerations and look at how physicians can use data pooling and federated learning to create more generalizable AI models.
Data Sharing from a Physician's Perspective
By: Ross Filice, MD
- Understand why physicians should care about data sharing.
- Discover two methods to improve generalizability of AI models.
- Grasp the pros and cons of data pooling.
- Learn the pros and cons of federated learning.
An IT Member's Perspective on Data Sharing
By: Brian Baker, BS
- Understand a five-tiered approach to data sharing.
- Learn best practices for IT members to safely share data.
Patient Perspective on Privacy & Data Sharing
By: Andrea Borondy-Kitts, MS, MPH
- Understand key patient considerations and concerns when sharing data for AI.
- Identify new trends likely to impact data sharing.
- Learn how to increase patient participation in data sharing.
- Discover different sources of digital health-related data.
- Know what to include in data sharing agreements with patients.
A Lawyer’s Perspective on Data Sharing
By: Tom Hoffman, JD, CAE
- Comprehend the top challenges and opportunities with data sharing and privacy.
- Learn the importance of defining who owns patient data.
- Understand why physicians might not share data, even if they have the legal right to do so.