Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …

Breast cancer is the primary cause of death in most cancer affected women. Mammography
is one of the most dependable strategies for early detection and diagnosis of breast cancer …

In this paper, a new adaptive neural network classifier (ANNC) of EEGP300 signals from
mental activities is proposed. To overcome an overtraining of the classifier caused by noisy …

ABSTRACT A huge increase in health issues has set new challenges to clinical routine for
patient's record about diagnosis, treatment and follow-up, with help of data & image …

Breast cancer has been most persistent form of common cancer in women. It is also the
leading cause of fatality in women each year. Breast cancer is much less common in …

Masses are one of the prevalent early signs of breast cancer, visible in mammogram.
However, its variation in shape, size, and appearance often creates hazards in proper …

This paper investigates detection of Architectural Distortions (AD) and spiculated masses in
mammograms based on their physical characteristics. We have followed a model based …

Medicine is one of the major fields where the application of artificial intelligence primarily
deals with construction of programs that perform diagnosis and make therapy …

In the existing research of mammogram image classification either clinical data or image
features of specific type is considered along with the supervised classifiers such as Neural …

Radiologists are interested in finding the stage of cancer, so the patient can be treated and
cured accordingly. This is possible by finding the type of abnormality to measure the severity …