DeepHealth partners with CARPL.ai to enhance AI safety in radiology

In a significant strategic move announced on December 1, 2024, DeepHealth, a subsidiary of RadNet based in the United States, has entered into a collaboration with CARPL.ai, known for its expertise in AI orchestration. This partnership aims to create an Artificial Intelligence control system tailored for image interpretation, assuring scalability and performance monitoring of AI in medical imaging. The initiative is geared towards ensuring patient safety and improving operational efficacy in radiology projects. Their collaborative efforts will focus on developing a closed-loop AI feedback system that continuously assesses the accuracy of AI models deployed in clinical environments. DeepHealth currently oversees the operational performance of its SmartMammo™ AI solution, which enhances breast cancer detection at RadNet imaging centers. The introduction of CARPL.ai’s technology into DeepHealth’s operations is expected to facilitate a streamlined experience for radiologists by integrating AI with existing workflows, making it more user-friendly while also optimizing patient outcomes. By combining the strengths of DeepHealth's cloud-native operating system, known as DeepHealth OS, with CARPL.ai’s orchestration tools, this partnership will produce a robust infrastructure to support the increasing use of AI in clinical radiology. Furthermore, the collaboration underscores the critical need for effective AI oversight in medical practices, especially in radiology. The companies emphasize that ongoing performance tracking of AI technologies is vital to ensure that these systems remain reliable and accurate over time. DeepHealth and RadNet employees, including radiologists and technologists, number over 10,000, demonstrating the scale at which patient care and AI integration are being revolutionized. Ultimately, this partnership is part of a broader trend in healthcare where AI solutions are increasingly incorporated into daily operations, aiming not only to enhance efficiency but also to push the boundaries of disease detection capabilities. The integration of AI technologies promises to transform patient care experiences, improve early detection of diseases, and streamline healthcare processes, reflecting the evolving landscape of medical technology. The forthcoming AI control system will likely play a pivotal role in this transformation, facilitating a safer and more effective use of artificial intelligence in the delivery of healthcare services.