Evaluation & Certification

Evaluation & Certification

Medical AI Quality Assessment and Compliance Hub: Ensuring and Elevating Healthcare Standards with AI

The Medical AI Quality Assessment and Compliance Hub is a specialized platform dedicated to enhancing the quality and reliability of Machine Learning applications in healthcare. Our mission is to ensure that medical AI technologies not only achieve clinical excellence but are robust, replicable, and adhere to ethical and legal standards. We provide a pivotal space for medical researchers and tech developers to rigorously evaluate and improve the quality of their medical AI systems, from basic Machine Learning research and model development to optimization, evaluation, and deployment, thereby building trust and confidence among healthcare professionals and patients.

Our services are based on our extensive experience in the field of Machine Learning best-practices1, 2 and ecosystem building3 and tailored to address the unique challenges and opportunities in medical AI. In collaboration with the the Faculty of Law (Prof. Pohlmann, Münster), we build infrastructure incorporating the evolving healthcare regulations on AI applications in medical settings.

  1. Hahn, T., Nierenberg, A. A., & Whitfield-Gabrieli, S. (2017). Predictive analytics in mental health: applications, guidelines, challenges and perspectives. Molecular psychiatry, 22(1), 37-43. ↩︎

  2. Hahn, T., Ebner-Priemer, U., & Meyer-Lindenberg, A. (2018). Transparent artificial intelligence–a conceptual framework for evaluating ai-based clinical decision support systems. Available at SSRN 3303123. ↩︎

  3. Winter, N. R., Cearns, M., Clark, S. R., Leenings, R., Dannlowski, U., Baune, B. T., & Hahn, T. (2021). From multivariate methods to an AI ecosystem. Molecular psychiatry, 26(11), 6116-6120. ↩︎