MAIA: A Collaborative Medical AI Platform for Integrated Healthcare Innovation

TL;DR

MAIA is an open-source, modular platform built on Kubernetes that facilitates interdisciplinary collaboration, data management, and deployment of AI models in healthcare, aiming to accelerate clinical AI translation.

Contribution

This paper introduces MAIA, a scalable, interoperable platform designed to bridge AI research and clinical practice through collaborative tools and real-world healthcare integrations.

Findings

Successful deployment in academic and clinical settings.

Enhanced collaboration among clinicians, researchers, and developers.

Supports real-world medical imaging AI projects.

Abstract

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.