Background Machine learning (ML) has become a vital part of medical imaging research.
ML methods have evolved over the years from manual seeded inputs to automatic …

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 …

Background Automatic segmentation and localization of lesions in mammogram (MG)
images are challenging even with employing advanced methods such as deep learning …

Objectives The objective of this study was to develop and validate a state-of-the-art, deep
learning (DL)-based model for detecting breast cancers on mammography. Methods …

Pathologists need a lot of clinical experience and time to do the histopathological
investigation. AI may play a significant role in supporting pathologists and resulting in more …

Choice Recommended Title, January 2021 This book, written by authors with more than a
decade of experience in the design and development of artificial intelligence (AI) systems in …

Designing computer-assisted diagnosis (CAD) systems that can precisely identify lesions
from mammography images would be useful for clinicians. Considering the morphological …

Background To determine if mammographic features from deep learning networks can be
applied in breast cancer to identify groups at interval invasive cancer risk due to masking …

Breast cancer death rates are higher due to the low accessibility of early detection
technologies. From the medical point of view, mammography diagnostic technology …

Early detection of esophageal cancer is of great significance for improving the survival rate
of esophageal cancer patients, and the esophageal cancer detection model based on deep …