This study aims to develop an efficient and accurate breast cancer classification model using
meta-learning approaches and multiple convolutional neural networks. This Breast …

Gait is commonly defined as the movement pattern of the limbs over a hard substrate, and it
serves as a source of identification information for various computer-vision and image …

Lung cancer is the most significant cancer that heavily contributes to cancer-related mortality
rate, due to its violent nature and late diagnosis at advanced stages. Early identification of …

(1) Background: In this paper, an artificial neural network approach for effective and real-
time quantitative microwave breast imaging is proposed. It proposes some numerical …

Generative artificial intelligence, especially with regard to the generative adversarial network
(GAN), is an important research area in radiology as evidenced by a number of literature …

Purpose One of the leading causes of death among women is breast cancer. However, it
has been established that early diagnosis with accurate results can ensure the prolonged …

Computed tomography (CT) images are the most commonly used radiographic imaging
modality for detecting and diagnosing lumbar diseases. Despite many outstanding …

Mammography is one of the imaging modalities used in diagnosing breast cancer at an
earlier stage. Misdiagnosis leads to risks for the patients. Better feature extraction and …

Internet of Things (IoT) plays an essential role in the area of the healthcare system. IoT
devices provide information about patients in the healthcare monitoring framework …

Deep Learning (DL) has rapidly become a methodology of choice for analyzing medical
images and increasingly attracts researchers' attention in the medical research community …