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Sonodynamic therapy (SDT) is a new therapeutic modality for the noninvasive cancer treatment based on the association of ultrasound and sonosensitizer drugs. Topical SDT requires the development of delivery systems to properly transport the sonosensitizer, such as zinc phthalocyanine (ZnPc), to the skin. In addition, the delivery system itself can participate in sonodynamic events and influence the therapeutic response. This study aimed to develop ZnPc-loaded micelle to evaluate its potential as a topical delivery system and as a cavitational agent

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Simulation-based methods such as approximate Bayesian computation (ABC) are well-adapted to the analysis of complex scenarios of populations and species genetic history. In this context, supervised machine learning (SML) methods provide attractive statistical solutions to conduct efficient inferences about scenario choice and parameter estimation. The Random Forest methodology (RF) is a powerful ensemble of SML algorithms used for classification or regression problems. Random Forest allows conducting inferences at a low computational c