Microwave radiation and the brain: Mechanisms, current status, and future prospects

S Mumtaz, JN Rana, EH Choi, I Han - International journal of molecular …, 2022 - mdpi.com
Modern humanity wades daily through various radiations, resulting in frequent exposure and
causing potentially important biological effects. Among them, the brain is the organ most …

Machine learning for healthcare radars: Recent progresses in human vital sign measurement and activity recognition

S Ahmed, SH Cho - IEEE Communications Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The unprecedented non-contact, non-invasive, and privacy-preserving nature of radar
sensors has enabled various healthcare applications, including vital sign monitoring, fall …

[HTML][HTML] Classification of Alzheimer's disease using MRI data based on Deep Learning Techniques

SE Sorour, AA Abd El-Mageed, KM Albarrak… - Journal of King Saud …, 2024 - Elsevier
Alzheimer's Disease (AD) is a worldwide concern impacting millions of people, with no
effective treatment known to date. Unlike cancer, which has seen improvement in preventing …

[HTML][HTML] Prediction and classification of Alzheimer disease categories using integrated deep transfer learning approach

M Leela, K Helenprabha, L Sharmila - Measurement: Sensors, 2023 - Elsevier
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects memory
and cognitive function. Early diagnosis of AD is important for timely intervention and …

Evaluation of unobtrusive microwave sensors in healthcare 4.0—toward the creation of digital-twin model

S Khan, IM Saied, T Ratnarajah, T Arslan - Sensors, 2022 - mdpi.com
The prevalence of chronic diseases and the rapid rise in the aging population are some of
the major challenges in our society. The utilization of the latest and unique technologies to …

A machine learning-based classification method for monitoring Alzheimer's disease using electromagnetic radar data

R Ullah, Y Dong, T Arslan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Alzheimer's and Parkinson's diseases are two neurodegenerative brain disorders affecting
more than 50 million people globally. Early diagnosis and appropriate assessment of …

Adversarial Network-Based Classification for Alzheimer's Disease Using Multimodal Brain Images: A Critical Analysis

M Gupta, R Kumar, A Abraham - IEEE Access, 2024 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that represents a
significant and growing public health challenge. This work concisely summarizes AD …

A numerical study of lossy multipole Debye dispersive media using a recursive integral-FDTD method

G Xie, M Fang, Z Huang, X Wu, X Ren… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A dispersive finite-difference time-domain (FDTD) method based on the recursive integration
(RI) technique for the modeling of the lossy multipole Debye dispersive media is described …

Review on machine learning techniques for medical data classification and disease diagnosis

S Saturi - Regenerative Engineering and Translational Medicine, 2023 - Springer
Purpose Machine learning (ML) has become a major trend in the industry because it is a
new and extremely advanced technical application. Design ML is utilized in various areas …

[HTML][HTML] Analysis of computational intelligence approaches for predicting disease severity in humans: Challenges and research guidelines

G Narasimhan, A Victor - Journal of Education and Health …, 2023 - journals.lww.com
The word disease is a common word and there are many diseases like heart disease,
diabetes, breast cancer, COVID-19, and kidney disease that threaten humans. Data-mining …