MAIA: A Collaborative Medical AI Platform for Integrated Healthcare Innovation
This addresses the problem of bridging technical innovation and practical healthcare applications for clinicians, researchers, and AI developers, but it is incremental as it builds on existing technologies like Kubernetes.
The paper tackles the challenge of integrating AI into clinical workflows by introducing MAIA, an open-source collaborative platform that facilitates interdisciplinary work among clinicians, researchers, and developers, with deployments in academic and clinical settings.
The integration of Artificial Intelligence (AI) into clinical workflows requires robust collaborative platforms that are able to bridge the gap between technical innovation and practical healthcare applications. This paper introduces MAIA (Medical Artificial Intelligence Assistant), an open-source platform designed to facilitate interdisciplinary collaboration among clinicians, researchers, and AI developers. Built on Kubernetes, MAIA offers a modular, scalable environment with integrated tools for data management, model development, annotation, deployment, and clinical feedback. Key features include project isolation, CI/CD automation, integration with high-computing infrastructures and in clinical workflows. MAIA supports real-world use cases in medical imaging AI, with deployments in both academic and clinical environments. By promoting collaborations and interoperability, MAIA aims to accelerate the translation of AI research into impactful clinical solutions while promoting reproducibility, transparency, and user-centered design. We showcase the use of MAIA with different projects, both at KTH Royal Institute of Technology and Karolinska University Hospital.