Israeli firm Aidoc is working with Nvidia to produce guidelines that can accelerate AI adoption across the healthcare industry.

Slated for release in early 2025, the Blueprint for Resilient Integration & Deployment of Guided Excellence (Bridge) guidelines will provide a robust, evidence-driven framework for seamlessly integrating AI into clinical workflows, helping healthcare organisations scale AI innovation with greater speed and confidence.

The guidelines aim to help establish clear pathways for healthcare systems to harness the potential of AI in improving patient outcomes.

Despite the approval of more than 900 FDA-cleared AI tools for medical imaging, healthcare systems remain mired in fragmentation, operational inefficiencies and scalability issues. The Bridge guidelines will provide a comprehensive, vendor-neutral roadmap, helping address these persistent challenges and empowering providers to unlock AI’s potential.

A key problem for many AI products has been the failure to scale effectively because critical considerations around integration were not addressed early enough in the development process. The guidelines will provide healthcare systems with direction on addressing scalability and interoperability from the start, enabling the implementation of AI across multiple sites simultaneously.

“AI holds the potential to revolutionise patient care, but its progress has been stalled by fragmented systems and the inability to scale effectively,” said Demetri Giannikopoulos, chief transformation officer at Aidoc. “The Bridge guidelines will focus on breaking down these barriers, offering a powerful, evidence-based framework that health systems can rely on not just to adopt AI but to help scale it across their operations. This will drive both operational efficiency and significantly better outcomes for patients and clinicians alike.”

While many existing guidelines focus on governance, regulatory concerns and responsible development practices, Bridge will be specifically designed to help developers and healthcare providers consider the practicalities of real-world deployment. This framework could empower organisations to navigate the complexities of AI adoption, from ideation to implementation and scalability across hospital systems.

This guidelines will help healthcare systems adopt and scale AI faster and more effectively by simplifying the design, validation, deployment and monitoring of AI tools. Key focus areas include:

• Standardised validation: Ensuring AI is rigorously tested for real-world use.
• Interoperability: Facilitating seamless integration of AI tools from different vendors.
• Scalable deployment: Providing a roadmap for efficient AI expansion across hospital systems.
• Continuous monitoring: Offering best practices to maintain AI accuracy post-deployment.

The guidelines will lay the groundwork for aligning to industry frameworks, such as MonAI, to build the blueprint for the medical AI enterprise platform. MonAI, co-founded by academia and industry, including Nvidia (www.nvidia.com), in 2019, provides the essential tools for medical AI development, validation and deployment, and provides a foundation for building the Bridge guidelines. With more than three million downloads and being used in FDA-approved software-as-medical-device applications, MonAI (monai.io) and its standardisation, interoperability and scalability are key to transformations in healthcare.

The guidelines will be developed through collaboration with healthcare providers, academic partners and industry leaders. This effort will leverage the expertise and experience from real-world AI initiatives to help ensure the framework is practical, actionable and scalable. By focusing on real-world challenges in AI integration, the guidelines aim to provide a comprehensive and adaptable approach for healthcare organisations.

Learn more about the Bridge guidelines at info.aidoc.com/bridge-guidelines.

Aidoc (Aidoc.com) focuses on aiding and empowering healthcare teams to optimise patient treatment, which results in improved economic value and clinical outcomes. Using Aidoc’s proprietary AIOs (www.aidoc.com/platform/aios), it analyses and aggregates medical data to enable care teams to operationalise the unexpected and work seamlessly with a continued focus on the patient.