Explaining the unique nature of individual gait patterns with deep learning

Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems. However, in most cases this comes with the disadvantage of acting as a black box, rarely providing information about what made them arrive at a particular prediction. This black box aspect of ML techniques can be problematic especially in medical diagnoses, so far hamperi

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ethics.ai (20 February 2019), “Explaining the unique nature of individual gait patterns with deep learning,” evidence record 8619, https://ethics.ai/record/8619 (originally published by OpenAlex).

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