Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy. (arXiv:2208.05232v2 [cs.HC] UPDATED)

Three-dimensional clinical gait analysis is essential for selecting optimal
treatment interventions for patients with cerebral palsy (CP), but generates a
large amount of time series data. For the automated analysis of these data,
machine learning approaches yield promising results. However, due to their
black-box nature, such approaches are often mistrusted by clinicians. We
propose gaitXplorer, a visual analytics approach for the classification of
CP-related gait patterns that integrates Grad-CAM, a well-established
explainable artificial intelligence algorithm, for explanations of machine
learning …

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