Machine Learning-Based Classification of Abnormal Liver Tissues Using Relative Permittivity.

ABSTRACT: The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measur

SUBMITTER: Samaddar P 

PROVIDER: S-EPMC9781624 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature