Explaining Machine Learning Models for Clinical Gait Analysis


The scientific work "Explaining Machine Learning Models for Clinical Gait Analysis", with the support of iToBoS project, has been published.

The article, by Djordje Slijepcevic, Fabian Horst, Sebastian Lapuschkin, Brian Horsak, Anna-Maria Raberger, Andreas Kranzl, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn and Matthias Zeppelzauer from Fraunhofer HHI, is presented in ACM Transactions on Computing in Healthcare, Vol 3, No.2 Article No. 14, pp 1-27.

All the details at ACM Transactions on Computing for Healthcare or at Scientific Publications section.