RDNT Stock Up Following the New Tie-Up to Leverage Radiology AI

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RadNet, Inc. RDNT yesterday announced that its wholly-owned subsidiary, DeepHealth, Inc., has partnered with artificial intelligence (AI) orchestration company, CARPL.ai. The collaboration aims to create a unique AI control system for image interpretation to ensure AI scalability, performance monitoring and safety to accelerate the adoption of AI.

It should be noted that DeepHealth currently monitors the performance of its SmartMammo AI-powered solution for breast cancer detection at RDNT. Through the collaboration, the two companies aim to expand, productize and scale this control system across more applications to other customers.

The announcement of the latest collaboration is a significant stepping stone for RadNet to strengthen its foothold in the global radiology AI space.

Likely Trend of RDNT Stock Following the News

Following the announcement on Dec. 1, shares of the company gained nearly 0.1% in today’s pre-market trading.

Historically, the company has gained a high level of synergies from its various collaborations. We expect market sentiment on the stock to continue to remain positive around this announcement, too.

RadNet currently has a market capitalization of $6.11 billion. Its projected earnings per share growth of 19.3% is higher than the industry’s 14.2%. In the last reported quarter, RDNT delivered an earnings surprise of 20%.

Rationale Behind RadNet’s Tie Up

Per RDNT, DeepHealth is expected to use CARPL.ai’s technology to develop an AI control system that can be commercialized and will be designed to monitor and optimize imaging AI performance for improved clinical outcomes, operational efficiency and accelerated adoption of AI in radiology. AI monitoring is crucial to ensure reliable, accurate and unbiased performance.

The two companies will likely collaborate on a new closed-loop AI feedback system that will continually monitor AI model accuracy and relevance in clinical settings. The system will automate the measurement and monitoring of performance and safety metrics such as specificity, sensitivity, data- and model drift.

Per RadNet’s management, DeepHealth’s partnership with CARPL.ai is expected to address the need of running multiple AI models (even for a single use case) by creating a unique environment to dynamically run a combination of models and monitor performance and then continuously optimize the best models for specific tasks.

CARPL.ai’s management believes that the partnership with DeepHealth will likely aid in harnessing the transformative potential of AI within the radiology care continuum, particularly through workflow automation and clinical assistance.