Microwave (MW) technologies are increasingly being employed in biomedicine and health care. Applications such as MW ablation (MWA), MW sensors for the realtime monitoring of physiological parameters, and lab-on-a-chip devices are just some of the examples in a wide variety of possibilities. Recently, highfrequency irreversible electroporation (H-FIRE) has been attracting more attention due to its important applications in oncology. It uses pulsed electrical fields (PEFs) to induce a controlled but irreversible process of permeabilization of cell membranes, thus triggering a substantial alteration in the physiological equilibria of cells, ultimately leading to their death.

Machine Learning for H-FIRE Protocols

Zappatore, M;Cerfeda, G;Tarricone, L
2021-01-01

Abstract

Microwave (MW) technologies are increasingly being employed in biomedicine and health care. Applications such as MW ablation (MWA), MW sensors for the realtime monitoring of physiological parameters, and lab-on-a-chip devices are just some of the examples in a wide variety of possibilities. Recently, highfrequency irreversible electroporation (H-FIRE) has been attracting more attention due to its important applications in oncology. It uses pulsed electrical fields (PEFs) to induce a controlled but irreversible process of permeabilization of cell membranes, thus triggering a substantial alteration in the physiological equilibria of cells, ultimately leading to their death.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/479670
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