Prediction of Cellular Malignancy Using Electrical Impedance Signatures and Supervised Machine Learning

ArXi:2601.04478v4 Announce Type: replace-cross Bioelectrical properties of cells such as relative permittivity, conductivity, and characteristic time constants vary significantly between healthy and malignant cells across different frequencies. These distinctions provide a promising foundation for diagnostic and classification applications. This study systematically reviewed 20 scholarly articles to compile 535 datasets of quantitative bioelectric parameters in the kHz-MHz frequency range and evaluated their utility in predictive modeling.