In the second edition of our White Paper Series, we discuss why user feedback should be implemented in the product development process and how to do it in a way that is most effective.
M3i and its partners, Munich Innovation Labs and the Munich University Hospital are excited to announce the publication of their first co-authored article, “Vibroarthrography for early detection of knee osteoarthritis using normalized frequency features” at Springer Nature (see here for a free, full length read-only version). The article discusses the findings from research project “ArthroScan”, conducted by researchers from M3i and the Munich University Hospital. In this EU-funded project, researchers sought to study the possibilities of vibroarthography, a non-invasive, non-radiative and very cost-effective technology using sound waves for early-stage detection of damage in knee joints. Munich Innovation Labs contributed its expertise in machine learning to the project, to develop a technology based on machine learning and a linear support vector machine, which proved to reach a classification specificity of approximately 0.8 at a sensitivity of 0.75. This performance is comparable to existing diagnostic tools, thus qualifying machine-learning- supported vibroarthography as an additional diagnostic tool.
M3i has officially been awarded as the winner of the German Federal Government’s Industry-in-Clinic National Initiative in 2016.