The use of metamaterials in various devices has revolutionized applications in optics,
healthcare, acoustics, and power systems. Advancements in these fields demand novel or …

Research on lung cancer automatic detection using deep learning algorithms has achieved
good results but, due to the complexity of tumor edge features and possible changes in …

In this paper, a novel technique for detecting female breast anomalous tissues is presented
and validated through numerical simulations. The technique, to a high degree, resembles X …

Microwave (MW) breast imaging has been investigated as a complementary breast
diagnosis modality for more than 30 years, and it is still an active field of research. We …

The research paper introduces a deep learning approach for distinguishing between benign
and malignant breast tissues using Ultra Wide Band (UWB) microwave imaging. A multi …

Wearable devices are currently of great importance in developing health management and
care applications and devices especially for early breast cancer detection (BCD). This is …

Since metasurface antennas are composed of ensembles of electrically-small resonators,
they have a tendency to be frequency band-limited. While this may be a significant …

In this paper, we have explored the utilization of an electrically small low-frequency
magnetic source for breast cancer detection. The object under test is a numerically realistic …

This paper introduces a novel system relying on an unsupervised approach to categorize
breast impressions obtained using low-frequency electromagnetic fields (LFEMF). We …

Breast carcinoma is a commonly occurring medical condition, and early detection is
essential for successful treatment. In terms of forecasting the danger of breast cancer …