A machine learning approach to predict in vivo skin growth
Matt Nagle,
Hannah Conroy Broderick,
Adrian Buganza Tepole
et al.
Abstract:Since their invention, tissue expanders, which are designed to trigger additional skin growth, have revolutionised many reconstructive surgeries. Currently, however, the sole quantitative method to assess skin growth requires skin excision. Thus, in the context of patient outcomes, a machine learning method which uses non-invasive measurements to predict in vivo skin growth and other skin properties, holds significant value. In this study, the finite element method was used to simulate a typical skin expansion… Show more
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