Patients with breast cancer are prone to serious health-related complications with higher
mortality. The primary reason might be a misinterpretation of radiologists in recognizing …

Background Breast cancer is a major public health concern, and early diagnosis and
classification are critical for effective treatment. Machine learning and deep learning …

Breast cancer remains a global challenge, causing over 600,000 deaths in 2018 (ref.). To
achieve earlier cancer detection, health organizations worldwide recommend screening …

Breast cancer analysis implies that radiologists inspect mammograms to detect suspicious
breast lesions and identify mass tumors. Artificial intelligence techniques offer automatic …

Many studies have recently used several deep learning methods for detecting skin cancer.
However, hyperspectral imaging (HSI) is a noninvasive optics system that can obtain …

Since the 1990s, there has been a significant increase in the number of imaging
examinations as well as a related increase in the healthcare expenditure and the exposure …

This paper provides a critical review of the literature on deep learning applications in breast
tumor diagnosis using ultrasound and mammography images. It also summarizes recent …

Objective: This study aimed to evaluate an automated detection system to detect and classify
permanent teeth on orthopantomogram (OPG) images using convolutional neural networks …

Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and
mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of …

Artificial intelligence algorithms based on principles of deep learning (DL) have made a
large impact on the acquisition, reconstruction, and interpretation of MRI data. Despite the …