Aidoc launches community-aligned framework for clinical AI

AIDOC and NVIDIA have developed an open source framework designed to help heads of information heads of information and health systems governance to manage fragmentation – between suppliers, evaluation processes and IT strategies – which invariably occurs with the emergence of artificial intelligence for clinical uses.

The new executive, called Bridge, could help standardize validation, interoperability, scalability, deployment and continuous monitoring to help health systems to obtain faster and more successful AI adoption, Aidoc said in Tuesday.

Why it matters

Bridge means BluePrint for resilient integration and the deployment of guided excellence. The framework aims to help resolve the lack of shared definitions and expectations of deployment of AI and offers health systems and their suppliers a clear and consensus base to assess and integrate automatic learning platforms in the provision of health care.

Built in collaboration with NVIDIA, the framework describes the technical, regulatory, operational and confidence construction criteria that AI tools must respond to be considered healthy health.

Bridge can give health systems the structure they need to implement the AI ​​in complete safety and responsible, according to Dr EFSTathia Andrikopoulou, medical director of echocardiography at the Harborview Medical Center and Associate Professor of Medicine and Collaborative Intelligence at the University of Washington.

“The deployment of large-scale AI requires more than technical performance,” she said in a press release. “This requires confidence, transparency and system preparation.”

In addition to Andrikopoulou, experts from university hospitals and Ochsner Health contributed to the roadmap, Aidoc said.

“We are at a point where AI in health care must mature from experience to integration,” added Dr Leonardo Kayat Bittencourt, vice-president of innovation in the radiology department of university hospitals.

The framework guides hospitals that sail in the use of clinical AI to differentiate models and software systems, establishing best practices to ensure a minimum viable production environment, incorporating confidence construction mechanisms and scaling systems.

The biggest trend

While AI is already used more often at the care point, Aidoc and Nvidia endeavor in October to create a plan to accelerate the adoption of AI in terms of AI by developing a framework based on evidence.

AIDOC is an AI tool provider that incorporates real -time information directly into clinical workflows to help providers fill care in care and speed up patient access to treatment. NVIDIA offers many microservices that can be executed from the Cloud or on Site to integrate generative AI into existing applications, focusing on a variety of health care cases, including genomics, imagery and other care provision priorities, such as preview of the hospital readizers.

By developing Bridge in collaboration with suppliers, university partners and other leaders in industry, Aidoc and Nvidia declared that they were trying to rely on the AI ​​of real health and to focus on the current challenges encountered by existing clinical clinical integration.

At the same time as

“To securely deploy AI in health care, we need more than strong algorithms,” said Reut Yalon, Aidoc product manager in a statement. “We need a shared structure. … This helps industry align with what” good “looks like so that we can accelerate adoption without compromising security or performance.”

Kayat Bittencourt added: “Bridge gives health systems the bases they need to evolve in a responsible manner and the language to do it together.”

Andrea Fox is editor -in -chief of Healthcare It News.
E-mail: [email protected]
Healthcare It News is a publication of the Himss media.