Aidoc announced Monday that it is partnering with NVIDIA to develop a framework for more effective deployment and integration of artificial intelligence tools in healthcare.
The Blueprint for Resilient Integration and Deployment of Guided Excellence, or BRIDGE, a guideline that aims to accelerate the adoption of AI in healthcare.
WHY IT’S IMPORTANT
The Blueprint for Resilient Integration and Deployment of Guided Excellence, or BRIDGE, is expected to be released in early 2025, the companies say. It is intended to be a “robust, evidence-based framework for seamlessly integrating AI into clinical workflows,” they say, “to help healthcare organizations scale AI innovation with greater speed and confidence.”
The plan aims to provide clear pathways for healthcare systems to simplify the design, validation, implementation and monitoring of AI tools for faster adoption and scale.
According to Aidoc and NVIDIA, the guidelines focus on four key areas: standardized validation, interoperability, scalable implementation and continuous monitoring. They are intended to help align healthcare systems with other industry frameworks such as MONAI, which was co-developed in 2019 by NVIDIA and other academic and industry researchers.
BRIDGE will be developed in collaboration with providers, academic partners and other industry leaders, the companies say, building on real AI initiatives and addressing common AI integration challenges.
THE BIG TREND
One of the biggest challenges is scaling AI effectively, often because important integration considerations were not addressed early enough in the development process. The BRIDGE guideline is intended to help with scalability and interoperability early on, by helping implement AI solutions in multiple locations simultaneously.
Another has to do with fragmentation. The companies note that despite the approval of more than 900 FDA-approved AI tools for medical imaging, many providers are still unable to create a comprehensive and integrated AI plan. BRIDGE offers the opportunity to build a vendor-neutral roadmap to that goal, they say.
It will be designed for both developers and providers, helping them think through the practicalities of real-world deployments and deal with the complexities of AI adoption, Aidoc and NVIDIA said.
Aidoc has been busy. This past week, through its work with the Coalition for Health AI, it unveiled new advances in “model cards,” similar to ingredient and nutrition labels on food products, designed to enhance the output of artificial intelligence and machine learning models to standardize.
NVIDIA introduced more than two dozen new generative AI microservices earlier this year, targeting a variety of healthcare use cases (genomics, imaging, drug discovery), designed to help integrate AI into existing applications that can be run from the cloud or on-premises carried out. . It later integrated these microservices with AWS.
ON THE RECORD
“AI has the potential to revolutionize patient care, but its progress is hampered by fragmented systems and the inability to scale effectively,” said Demetri Giannikopoulos, Chief Transformation Officer at Aidoc in a statement.
“The BRIDGE Guidance will focus on breaking down these barriers and providing a powerful, evidence-based framework that healthcare systems can rely on to not only adopt AI, but also help scale it across their operations. This will drive both operational efficiency and significantly better results. for both patients and doctors.”
Mike Miliard is editor-in-chief of Healthcare IT News
Email the writer: mike.miliard@himssmedia.com
Healthcare IT News is a HIMSS publication.