Research in the medical imaging field using deep learning approaches has become
progressively contingent. Scientific findings reveal that supervised deep learning methods' …

Breast cancer is one of the most prevalent types of cancer that plagues females. Mortality
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …

The competitive airline sector has grown at a breakneck pace in the last two decades. A
useful source for collecting consumer feedback and performing various forms of analysis on …

Advances in deep learning networks, especially deep convolutional neural networks
(DCNNs), are causing remarkable breakthroughs in radiology and imaging sciences. These …

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue
characteristics and follow a well-understood path of technical, biological and clinical …

Breast cancer is one of the most common death causes amongst women all over the world.
Early detection of breast cancer plays a critical role in increasing the survival rate. Various …

In order to effectively aid in the automatic classification of the breast cancer suspicious
region, a new deep-learning (DL) model built on the transfer-learning (TL) technique is …

The accurate assessment or diagnosis of breast cancer depends on image acquisition and
image analysis and interpretation. The expert radiologist makes image interpretation, and …

Abstract Machine learning has made potential developments in biotechnology. Years of
medical training are required for correct diagnosis of diseases. Diagnostics is often a very …

Cancer instances have increased in the recent past and are risking many lives. Every kind of
cancer is caused due to a malignant (cancerous) tumor which looks pretty similar to a …