Aidoc and NVIDIA Unveil BRIDGE to Accelerate AI Adoption in Healthcare

Aidoc and NVIDIA have partnered to develop a new framework called BRIDGE (Blueprint for Resilient Integration and Deployment of Guided Excellence), designed to help healthcare organizations adopt and scale artificial intelligence (AI) across their operations. The companies announced that BRIDGE will provide a comprehensive, evidence-based guideline for integrating AI into clinical workflows.

Accelerating AI in Healthcare

The BRIDGE framework aims to simplify the deployment, validation, and monitoring of AI tools in healthcare, providing a clear pathway for faster and more scalable adoption of AI technologies. Expected to launch in early 2025, BRIDGE is intended to help healthcare organizations integrate AI into their clinical workflows with confidence and efficiency.

Key Focus Areas of BRIDGE

According to Aidoc and NVIDIA, BRIDGE will focus on four primary areas:

• Standardized Validation: Ensuring AI tools meet consistent performance and safety standards.

• Interoperability: Seamlessly integrating AI tools with existing healthcare systems.

• Scalable Deployment: Enabling healthcare providers to implement AI across multiple sites simultaneously.

• Continuous Monitoring: Providing ongoing oversight to ensure AI tools perform optimally and remain safe over time.

These guidelines will align with other industry frameworks, such as MONAI, co-developed by NVIDIA and researchers to promote AI in medical imaging. Aidoc and NVIDIA are collaborating with providers, academic institutions, and industry leaders to develop the BRIDGE framework based on real-world AI initiatives.

Tackling Fragmentation and Scalability

One of the main barriers to AI adoption in healthcare is the fragmentation of systems and the lack of integration planning. Despite the approval of over 900 FDA-cleared AI tools for medical imaging, many healthcare providers struggle to create a comprehensive AI strategy. BRIDGE is designed to help solve this problem by offering a vendor-neutral roadmap for AI integration, addressing challenges like scalability and interoperability early in the development process.

Broader Trends in AI and Healthcare

BRIDGE is part of a larger movement to make AI more accessible in healthcare. Aidoc recently collaborated with the Coalition for Health AI to introduce model cards, a new method for standardizing AI and machine learning outputs. NVIDIA has also been active in healthcare AI, launching over two dozen generative AI microservices earlier this year for genomics, imaging, and drug discovery. These services are designed to integrate with cloud and on-premise applications.

In Their Words

"AI holds the potential to revolutionize 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 guideline will focus on breaking down these barriers, offering a powerful, evidence-based framework that health systems can rely on to not just 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."

What This Means for AI in Healthcare

The introduction of the BRIDGE framework is a critical step toward addressing the ongoing challenges of AI adoption in healthcare. By providing a clear, evidence-based roadmap for integrating and scaling AI tools, Aidoc and NVIDIA are empowering healthcare organizations to move beyond fragmented systems and embrace AI's full potential. As AI becomes more ingrained in clinical workflows, BRIDGE could accelerate operational efficiency and improve patient outcomes, making AI a core component of healthcare delivery.