Breast cancer is one of the largest causes of women's death in the world today. Advance
engineering of natural image classification techniques and Artificial Intelligence methods …

We describe an automated methodology for the analysis of unregistered cranio-caudal (CC)
and medio-lateral oblique (MLO) mammography views in order to estimate the patient's risk …

Screening mammography is an important front-line tool for the early detection of breast
cancer, and some 39 million exams are conducted each year in the United States alone …

Detection of suspicious regions in mammogram images and the subsequent diagnosis of
these regions remains a challenging problem in the medical world. There still exists an …

Deep learning has recently attracted a lot of attention, mainly thanks to substantial gains in
terms of effectiveness. However, there is still room for significant improvement, especially …

For a long time, the detection of diabetic retinopathy has always been a great challenge.
People want to find a fast and effective computer-aided treatment to diagnose the disease. In …

In this project, we attempted to create a deep learning model to classify cervix types in order
to help healthcare providers provide better care to women all over the world. The problem is …

In recent years, deep learning has been used in many researches in cancer screening
based on medical imaging. Among cancer screening using optical imaging, melanoma …

This paper investigates the opportunities for applying deep learning networks to tumour
classification. It finds that simple networks can be found to deliver reasonable performance …

Breast cancer is the most lethal form of cancer among women. It is estimated that 520
thousand deaths are caused by this disease each year. Due to this, breast screening …