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Trustworthy and Responsible AI Network expands to help European healthcare organizations enhance the quality, safety and trustworthiness of AI in health

Emerging AI technologies hold significant promise for revolutionizing the healthcare sector in Europe and across the globe.

At HLTH Europe, the Trustworthy & Responsible AI Network (TRAIN), a consortium of healthcare leaders, announced its expansion to Europe with the objective 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.

Emerging AI technologies hold significant promise for revolutionizing the healthcare sector in Europe and across the globe. By enhancing patient care outcomes, streamlining processes and reducing costs, AI has the potential to transform the industry. 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.
  • 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.
  • Sharing 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 registration of AI used for clinical care or clinical operations through a secure online portal.
  • Providing 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 of 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.
  • Working toward the development of a federated AI outcomes registry for organizations to share among themselves. The registry will capture real-world outcomes related to efficacy, safety and optimization of AI algorithms.

For more information on European TRAIN, join us at HLTH Europe on Tuesday, June 18, from 12:30 to 12:40 p.m. CEST at The Forum stage (H90), where we’ll share more details about the network and its objectives.

TRAIN member quotes:

“Transforming healthcare using AI must be seen as a global challenge that requires worldwide cross-border collaborations. This approach is an important step that enables us to tackle challenges not only at the national level, but also across the EU and globally. To truly warrant bedside adoption, we must work together to ensure AI benefits all. Safeguards built into the technology will improve such equity.”  Dr. Michel van Genderen, attending intensivist at Erasmus Medical Center and co-founder of the Erasmus MC Datahub

“As an NGO dedicated to researching the use of AI in healthcare, Foundation 29 is deeply concerned with ensuring that the use of AI respects patient privacy and security. While high-quality data, often sourced from patients, is essential for advancing AI technologies, it is equally crucial to guarantee responsible use of this data. For us, safeguarding patient data and fostering a trustworthy environment for AI development and deployment in healthcare is of paramount importance.”  Sarah Harmon, president, Foundation 29

“AI has the potential to transform healthcare, but we must remain vigilant about its ethical implications. In TRAIN, we are joining forces across Europe to share knowledge and tools for successful and sustainable implementation of trustworthy and responsible AI into healthcare practices.” — Magnus Kjellberg, head of AI Competence Center, Sahlgrenska University Hospital

“TRAIN is a role model for joint efforts between the technology industry and healthcare. AI represents a strategy that gives hope for future healthcare effectiveness. The upcoming European TRAIN effort will be an opportunity to take a fundamental step forward to operationalize  responsible AI solutions by facilitating the generation and validation of algorithms with patient integrity left intact.”  Professor Stefan Jovings, M.D., Ph.D., president of research and education, Skane University Hospital, Sweden

“TRAIN’s focus on responsible AI principles and privacy-preserving collaboration enforces our strategies to safely and ethically leverage AI technologies. This initiative builds trust, protects patient data, and aligns the participating institutions’ practices to the European healthcare standards.”  Carlo Tacchetti, professor and coordinator, AI strategic program of UniSR and director of Experimental Imaging Center, San Raffaele Scientific Institute

“AI in healthcare needs collaborations on a national and an international level to help us use AI’s power for improving patient care and outcomes. We are excited to be part of this collaboration to contribute to the new era of medicine that awaits us.”  Ben Collignon, chief information officer, UMC Utrecht

“The primary goal for TRAIN is to enable individuals and organizations to operationalize responsible AI principles through technology-based guardrails. TRAIN will also enable organizations to collaborate through federated, privacy-preserving approaches. The formation of TRAIN in Europe will help foster trust and confidence in the application of AI in health and ensure that data privacy is maintained.” — David Rhew, M.D., chief medical officer and vice president of healthcare, Microsoft

About the Trustworthy & Responsible AI Network (TRAIN)

The Trustworthy & Responsible AI Network (TRAIN) is one of the first health AI networks aimed at operationalizing responsible AI principles. Through collaboration, TRAIN members will help improve the quality, safety, and trustworthiness of AI in health by sharing best practices, enabling registration of AI used for clinical care or clinical operations, providing tools to enable measurement of outcomes associated with the implementation of AI, and facilitating the development of a federated AI outcomes registry for organizations to share amongst themselves.

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