Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we
conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) …

Deep learning analysis of radiological images has the potential to improve diagnostic
accuracy of breast cancer, ultimately leading to better patient outcomes. This paper …

Early diagnosis of breast lesions and differentiation of malignant lesions from benign lesions
are important for the prognosis of breast cancer. In the diagnosis of this disease ultrasound …

Artificial intelligence (AI) has invaded our daily lives, and in the last decade, there have been
very promising applications of AI in the field of medicine, including medical imaging, in vitro …

Breast cancer is the most frequently diagnosed cancer in women; it poses a serious threat to
women's health. Thus, early detection and proper treatment can improve patient prognosis …

The purpose of this study was to use the Coronavirus Disease 2019 (COVID-19) Reporting
and Data System (CO-RADS) to evaluate the chest computed tomography (CT) images of …

Deep learning (DL) is one of the most powerful data-driven machine-learning techniques in
artificial intelligence (AI). It can automatically learn from raw data without manual feature …

Millions of breast imaging exams are performed each year in an effort to reduce the
morbidity and mortality of breast cancer. Breast imaging exams are performed for cancer …

Objective Although artificial intelligence (AI) has demonstrated promise in enhancing breast
cancer diagnosis, the implementation of AI algorithms in clinical practice encounters various …

Purpose We aimed to evaluate deep learning approach with convolutional neural networks
(CNNs) to discriminate between benign and malignant lesions on maximum intensity …