Aidoc announced Monday that it is collaborating with NVIDIA to develop a framework for more effective deployment and integration of artificial intelligence tools in healthcare.
Guided Excellence (BRIDGE) Resilient Integration and Deployment Blueprint. These are guidelines aimed at accelerating AI adoption across the healthcare industry.
Why is it important?
The companies say the Guided Excellence (BRIDGE) Resilient Integration and Deployment Blueprint is expected to be released in early 2025. It aims to be a “robust, evidence-based framework for seamlessly integrating AI into clinical workflows” and “helps healthcare organizations scale AI innovations more quickly and reliably,” they said. There is.
The plan aims to set a clear path for health systems, simplify the design, validation, deployment, and monitoring of AI tools, and speed adoption and scale.
According to Aidoc and NVIDIA, the guidelines focus on four key areas: standardized validation, interoperability, scalable deployment, and continuous monitoring. These are intended to enable health systems to collaborate with other industry frameworks, such as MONAI, which was jointly developed by NVIDIA and other academic and industry researchers in 2019.
The companies say BRIDGE was developed in collaboration with providers, academic partners, and other industry leaders, builds on real-world AI initiatives, and focuses on common challenges in AI integration.
bigger trends
One of their biggest challenges is effectively scaling AI. This is often because important integration considerations are not addressed early enough in the development process. The BRIDGE guidelines are intended to support early scalability and interoperability, and support simultaneous implementation of AI solutions across multiple sites.
The other has to do with fragmentation. The companies note that despite more than 900 FDA-cleared AI tools for medical imaging, many providers have yet to build a comprehensive, integrated AI plan. They say BRIDGE offers an opportunity to build a vendor-neutral roadmap toward that goal.
According to Aidoc and NVIDIA, it is designed for both developers and providers to help them think through the practicalities of real-world deployments and navigate the complexities of AI adoption.
Idoc is busy. Last week, through a collaboration with the Coalition for Health AI, the company announced new advances in “model cards,” similar to food ingredient and nutrition labels, designed to standardize the artificial intelligence and machine learning models it outputs. Announced.
Earlier this year, NVIDIA announced more than 20 new innovations focused on a variety of healthcare use cases (genomics, imaging, drug discovery) designed to help you integrate AI into existing applications that can run from the cloud or on-premises. Introduced generative AI microservices. . We then integrated these microservices with AWS.
On record
“AI has the potential to revolutionize patient care, but progress is slowed by fragmented systems and inability to scale effectively,” Demetri Giannikopoulos, Aidoc's chief transformation officer, said in a statement. “I am doing so,” he said.
“The BRIDGE Guidelines focus on breaking down these barriers and provide a strong, evidence-based framework that health systems can rely on to not only adopt AI, but extend AI across their operations. This drives both operational efficiency and significantly better outcomes for patients and clinicians alike. ”
Mike Miliard is the Editor-in-Chief of Healthcare IT News
Email the author: mike.miliard@himssmedia.com
Healthcare IT News is a HIMSS publication.
