Abstract: Systems and methods for detecting dielectric changes in matter are provided. The system includes a data collection array to collect microwave scattering data and a machine learning device. The machine learning device is configured to receive the microwave scattering data, patient information, and imaging modality data corresponding to at least one of a presence of disease, absence of disease, or one or more disease features; analyze the microwave scattering data, patient information, and imaging modality data; output at least one of a predicted disease state and predicted features based on the analyzed microwave scattering data, patient information, and imaging modality data; compare the imaging modality data corresponding to the at least one of a presence of disease, absence of disease, or one or more disease features to the predicted disease state or predicted features; and use the comparison as an input into the machine learning device.

Abstract: Systems and methods for detecting dielectric changes in matter are provided. The system includes a data collection array to collect microwave scattering data and a machine learning device. The machine learning device is configured to receive the microwave scattering data, patient information, and imaging modality data corresponding to at least one of a presence of disease, absence of disease, or one or more disease features; analyze the microwave scattering data, patient information, and imaging modality data; output at least one of a predicted disease state and predicted features based on the analyzed microwave scattering data, patient information, and imaging modality data; compare the imaging modality data corresponding to the at least one of a presence of disease, absence of disease, or one or more disease features to the predicted disease state or predicted features; and use the comparison as an input into the machine learning device.