A machine learning framework for automated diagnosis and computer-assisted planning in plastic and reconstructive surgery. PGM Knoops, A Papaioannou, A Borghi, et al.
Date: September 2019. Source: Scientific Reports 9, 13597 (2019). Abstract: Current computational tools for planning and simulation in plastic and reconstructive surgery lack sufficient precision and are time-consuming, thus resulting in limited adoption. Although computer-assisted surgical planning systems help to improve clinical outcomes, shorten operation time and reduce cost, they are often too complex and…