Leveraging ensemble machine learning models (XGBoost and random forest) and genetic algorithms to predict factors contributing to the liposomal entrapment of therapeutics
Fatemeh Khodadadi, Fatemeh Taghizadeh, Ali Hashemi Baghi, Seyed Mohammad Ayyoubzadeh, Simin Dadashzadeh, Azadeh Haeri · Nanoscale · 2025
, and size. Moreover, the statistical analysis indicated the appropriateness of using the genetic algorithm to optimize the tree-based machine learning models. This optimization could facilitate the selection of appropriate parameters for analyzing the liposomization of various cargoes.