Related papers: Breast cancer detection using artificial intellige…

Breast cancer is the second leading cause of cancer-related death after lung cancer in women. Early detection of breast cancer in X-ray mammography is believed to have effectively reduced the mortality rate. However, a relatively high false…

Gastric cancer ranks as the fifth most common and fourth most lethal cancer globally, with a dismal 5-year survival rate of approximately 20%. Despite extensive research on its pathobiology, the prognostic predictability remains inadequate,…

Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis. The analysis of such images is not only time and resource consuming, but also very challenging even for experienced pathologists,…

Lung cancer (LC) ranks among the most frequently diagnosed cancers and is one of the most common causes of death for men and women worldwide. Computed Tomography (CT) images are the most preferred diagnosis method because of their low cost…

Screening mammograms are a routine imaging exam performed to detect breast cancer in its early stages to reduce morbidity and mortality attributed to this disease. In order to maximize the efficacy of breast cancer screening programs,…

Breast cancer remains the most commonly diagnosed malignancy among women in the developed world. Early detection through mammography screening plays a pivotal role in reducing mortality rates. While computer-aided diagnosis (CAD) systems…

Full-Field Digital Mammography (FFDM) is the primary imaging modality for routine breast cancer screening; however, its effectiveness is limited in patients with dense breast tissue or fibrocystic conditions. Contrast-Enhanced Spectral…

According to some medical imaging techniques, breast histopathology images called Hematoxylin and Eosin are considered as the gold standard for cancer diagnoses. Based on the idea of dividing the pathologic image (WSI) into multiple…

Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and…

In this study, we present an interpretable deep learning framework for the early detection of breast cancer using quantitative features extracted from digitized fine needle aspirate (FNA) images of breast masses. Our deep neural network,…

Cancer is a fatal disease caused by a combination of genetic diseases and a variety of biochemical abnormalities. Lung and colon cancer have emerged as two of the leading causes of death and disability in humans. The histopathological…

Background and Objective: Breast cancer, which accounts for 23% of all cancers, is threatening the communities of developing countries because of poor awareness and treatment. Early diagnosis helps a lot in the treatment of the disease. The…

Lung cancer, the second leading cause of cancer-related deaths, is primarily linked to long-term tobacco smoking (85% of cases). Surprisingly, 10-15% of cases occur in non-smokers. In 2020, approximately 2 million people were affected…

Molecular subtyping of breast cancer is crucial for personalized treatment and prognosis. Traditional classification approaches rely on either histopathological images or gene expression profiling, limiting their predictive power. In this…

Artificial intelligence is constantly evolving and can provide effective help in all aspects of people's lives. The experiment is mainly to study the use of artificial intelligence in the field of medicine. The purpose of this experiment…

Thyroid cancer is common worldwide, with a rapid increase in prevalence across North America in recent years. While most patients present with palpable nodules through physical examination, a large number of small and medium-sized nodules…

Breast cancer is the second most common type of cancer in women in Canada and the United States, representing over 25\% of all new female cancer cases. As such, there has been immense research and progress on improving screening and…

Cancer is an extremely difficult and dangerous health problem because it manifests in so many different ways and affects so many different organs and tissues. The primary goal of this research was to evaluate deep learning models' ability…

Deep learning object detection algorithm has been widely used in medical image analysis. Currently all the object detection tasks are based on the data annotated with object classes and their bounding boxes. On the other hand, medical…

We present a deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images). Our network achieves an AUC of 0.895 in predicting whether there is a…