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Rhino Health 2023
Facilitating the Creation of Healthcare AI Models via Edge Computing & Federated Learning
Author
Ryan Pretnik
Author
Josh Naegle
Author
Jacob Brown
Large, relevant data sets are very beneficial to building and training AI models, but data custodians’ desire to protect patient privacy and the privacy laws surrounding healthcare prevent easy access to robust data for healthcare innovators. Rhino Health’s edge computing and federated learning platform allows developers to use decentralized, encrypted data that sits behind custodian firewalls. This report offers an initial look at the experiences of healthcare professionals using the Rhino Health platform.
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Key Findings:
- Rhino Health Customer Experience: An Initial Look
- Points to Ponder
- Rhino Health: Company Profile at a Glance
- Solution Technical Specifications (provided by Rhino Health)
Project Manager
Robert Ellis
This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2024 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.