TRAIN Expands to Help European Healthcare Organizations

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. Organizations that have come together to form the European TRAIN include 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.

Foundation 29, a nonprofit organization that aims to empower patients and transform healthcare through data-driven initiatives and innovative technologies, has also joined European TRAIN. The network is open to other healthcare organizations in Europe interested in joining. As the technology continues to evolve, robust development and evaluation standards are crucial to ensure responsible and effective AI applications. TRAIN aims to improve the quality, safety, and trustworthiness of AI tools implemented in healthcare to help ensure clinicians and patients benefit from this innovative technology.

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 and working in collaboration with other TRAIN members and key stakeholders to enable all organizations, including low-resource settings, to benefit from technology-based responsible AI guardrails. The program also promises to share best practices related to the use of AI in healthcare settings, including the 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.

Working toward enabling the registration of AI used for clinical care or clinical operations through a secure online portal is another point of collaboration. TRAIN also offers tools to enable measurement of outcomes associated with the implementation of AI, including best practices for studying the efficacy and value of AI methods in healthcare settings and leveraging privacy-preserving environments, with considerations in both pre-and post-deployment settings. Tools that allow analyses to be performed in subpopulations to assess bias may also be provided. Finally, the program aims to work toward the development of a federated AI outcomes registry for organizations to share among themselves. The registry will capture real-world outcomes related to the efficacy, safety, and optimization of AI algorithms.