Microsoft Announces Expansion of AI Network Into HLTH Europe

Monday, at HLTH Europe, the Trustworthy & Responsible AI Network (TRAIN), a consortium of healthcare leaders, announced its expansion to Europe to help organizations in the region operationalize responsible AI through technology-based guardrails.

The European TRAIN includes organizations such as Erasmus MC (the Netherlands), HUS Helsinki University Hospital (Finland), Sahlgrenska University Hospital (Sweden), Skåne University Hospital (Sweden), Universita Vita-Salute San Raffaele (Italy), and University Medical Center Utrecht (the Netherlands), with Microsoft as the technology enabling partner.

Additionally, Foundation 29, a nonprofit organization seeking to transform healthcare through data-driven initiatives, has joined the network. According to the blog, TRAIN is open to other European healthcare organizations interested in joining.

Over the last few years, new AI technologies have shown significant promise for revolutionizing the healthcare sector globally. According to multiple studies and trials, AI has enhanced patient care outcomes, streamlined processes, and reduced costs.

TRAIN’s initial formation, announced in March 2024, introduced leading healthcare organizations in the U.S. as part of the network. The consortium’s operational objectives include:

• Providing technology and tools that enable trustworthy and responsible AI principles to be operationalized at scale.
• Collaborating with other TRAIN members and key stakeholders to ensure all organizations, including low-resource settings, benefit from technology-based responsible AI guardrails.
• Sharing best practices related to the use of AI in healthcare settings, including safety, reliability, and monitoring of AI algorithms, and the skillsets required to manage AI responsibly. Data and AI algorithms will not be shared between member organizations or with third parties.
• Enabling registration of AI used for clinical care or clinical operations through a secure online portal.
• Providing tools to measure outcomes associated with AI implementation, including best practices for studying the efficacy and value of AI methods in healthcare settings and leveraging privacy-preserving environments. Tools for analyzing subpopulations to assess bias may also be provided.
• Developing a federated AI outcomes registry for organizations to share among themselves, capturing real-world outcomes related to the efficacy, safety, and optimization of AI algorithms

But with that said, the need for robust development and evaluation standards has become more crucial as AI has scaled through healthcare. Due to this, TRAIN aims to improve the quality, safety, and trustworthiness of AI tools in healthcare, ensuring both clinicians and patients benefit from this innovative technology.

Responsible AI, practically in healthcare due to strong regulatory requirements sounding patient rights, healthcare data, etc. will continue to grow and evolve as time goes by. Microsoft’s move will be eyed by other leading AI leads in the short and medium terms.

At HLTH Europe, a consortium of healthcare leaders announced its expansion to Europe to help organizations in the region operationalize responsible AI through technology-based guardrails.

Originally posted on OpenDataScience.com

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