Classification of Alzheimer's disease using RF signals and machine learning
Objectives: Alzheimer's disease is one of the most fastest growing and costly diseases in the
world today. It affects the livelihood of not just patients, but those who take care of them …
world today. It affects the livelihood of not just patients, but those who take care of them …
Microwave breast cancer detection via cost-sensitive ensemble classifiers: Phantom and patient investigation
Microwave breast screening has been proposed as a complementary modality to the current
standard of X-ray mammography. In this work, we design three ensemble classification …
standard of X-ray mammography. In this work, we design three ensemble classification …
A time-domain microwave system for breast cancer detection using a flexible circuit board
A Santorelli, E Porter, E Kang, T Piske… - IEEE Transactions …, 2015 - ieeexplore.ieee.org
We present the design of a flexible multilayer circuit board for use in a custom-built
microwave system for breast health monitoring. The flexible circuit features both an …
microwave system for breast health monitoring. The flexible circuit features both an …
The diagnostic performance of machine learning in breast microwave sensing on an experimental dataset
T Reimer, S Pistorius - … , RF and Microwaves in Medicine and …, 2021 - ieeexplore.ieee.org
Objective: This paper assesses the diagnostic performance of deep learning methods for
tumour detection in breast microwave sensing (BMS). Methods: A convolutional neural …
tumour detection in breast microwave sensing (BMS). Methods: A convolutional neural …
Image-based classification of bladder state using electrical impedance tomography
Objective: In this study, we examine the potential of using machine learning classification to
determine the bladder state ('not full','full') with electrical impedance tomography (EIT) …
determine the bladder state ('not full','full') with electrical impedance tomography (EIT) …
Improving the diagnostic capability of microwave radar imaging systems using machine learning
T Reimer, J Sacristan, S Pistorius - 2019 13th European …, 2019 - ieeexplore.ieee.org
Breast microwave sensing (BMS) is a potential breast cancer detection technique that uses
low-power microwave radiation to detect the presence of cancerous lesions. This work …
low-power microwave radiation to detect the presence of cancerous lesions. This work …
Cost-sensitive ensemble classifiers for microwave breast cancer detection
Y Li, A Santorelli, O Laforest… - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
Microwave breast cancer detection involves analysing the scattered waveforms of
microwave signals that are propagated into the breast. We have developed a microwave …
microwave signals that are propagated into the breast. We have developed a microwave …
Improving image reconstruction and machine learning methods in breast microwave sensing
T Reimer - 2020 - mspace.lib.umanitoba.ca
Breast microwave sensing (BMS) is an emerging modality that has the potential to be used
as a breast cancer screening technique but challenges remain before the modality is …
as a breast cancer screening technique but challenges remain before the modality is …
Detection of food contaminants with Microwave Sensing and Machine Learning
L Urbinati - 2019 - webthesis.biblio.polito.it
Today, food contamination due to foreign body is still a trouble for food manufacturers. First
of all, because they have to guarantee a safe product to consumers. Secondly because a …
of all, because they have to guarantee a safe product to consumers. Secondly because a …
Investigation of Long Short-Term Memory Based Ultrawide Band Microwave Breast Tumor Size Prediction
Y Wu, H Zhu - 2019 12th International Congress on Image and …, 2019 - ieeexplore.ieee.org
Breast cancer is one of the most common malignancies among women in the world. Early
detection and reliable monitoring are important factors in improving the survival rate and …
detection and reliable monitoring are important factors in improving the survival rate and …