Healthcare AI Challenge

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Expert-led, data-driven AI evaluation for effective adoption in clinical care

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What is the Healthcare AI Challenge?

The Healthcare AI Challenge is a first of its kind, multi-institutional collaborative dedicated to the robust evaluation of clinical grade AI solutions. Interactive challenges are hosted on the Mass General Brigham AI Arena platform, enabling structured and transparent AI evaluation that empowers healthcare professionals to experience and assess cutting-edge AI in real-world clinical scenarios. Continuous, consistent, and reliable insights collected from clinical experts are used to inform adoption within provider organizations and improve AI agents.

See for yourself how the Healthcare AI Challenge is setting a new standard for evaluation of cutting-edge AI solutions.

Why Participate

Providers/Clinical End-Users

  • Receive early access to cutting-edge AI solutions and learn how they work
  • Evaluate AI performance on clinically relevant use cases and multi-institutional data
  • Explore how the latest AI tools could benefit future clinical care and research
  • Gain insights about how these solutions may impact workflows in the future
  • Help shape the future of healthcare by ensuring AI tools meet the high standards required for clinical implementation

Healthcare Organizations

  • Enable professionals within your organization to gain hand-on experience working with the latest AI solutions
  • Gain insights on model performance on real world use cases that go beyond static vendor demos or one-size-fits-all benchmarks to support smarter AI adoption decision making
  • Join network of peer institutions across the US leading the way and sharing best practices for scalable, robust evaluation of AI solutions

AI Developers

Public events allow you to:

  • Conduct post market performance monitoring
  • Demonstrate model capabilities to potential customers
  • Engage with the entire Healthcare AI Challenge community to solicit feedback on model performance

Private events allow you to:

  • Generate meaningful insights on AI performance (e.g. discordance, generalizability, bias) using diverse, real-world data to support model finetuning, prompt engineering
  • Validate both non-FDA AI applications and models requiring FDA clearance, from studies piloting readiness to complete validation studies ready for FDA submission
  • Solicit feedback directly from end users to support product design and prompt engineering
  • Compare model performance against competitors

Who can participate?

Participants must be affiliated with a US based healthcare organization (e.g. private practice, hospital, health system) that is a member of the Healthcare AI Challenge collaborative. See our full list of member institutions below.

Founding Members

Institutional Members

Sol Radiology

UAB Medicine

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