Evaluation of the morphological and biological functions of vascularized microphysiological systems with supervised machine learning.Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease.  The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function.  These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. 
machine learning
Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.
random forest regression