Microscopic examination of biopsy tissue slides is perceived as the gold-standard
methodology for the confirmation of presence of cancer cells. Manual analysis of an …

Artificial neurons used in Artificial Neural Networks and Deep Learning architectures do not
mimic the chaotic behavior of biological neurons found in the brain. Recently, a chaos based …

Breast cancer is the second deadliest cancer (after lung cancer) globally among women,
with high incidence and mortality rates. Its early diagnosis is pivotal for improving the cure …

Early detection and patient-driven precise treatment can drastically reduce the elevation in
the mortality rate due to breast tumours in women. Therefore, it is inevitable to develop an …

Breast Cancer, with an expected 42,780 deaths in the US alone in 2024, is one of the most
prevalent types of cancer. The death toll due to breast cancer would be very high if it were to …

Histopathological analysis is an essential exam for detecting various types of cancer. The
process is traditionally time-consuming and laborious. Taking advantage of deep learning …

Breast cancer remains a global concern, underscoring the crucial need for early diagnosis to
ensure effective treatment. In recent years, convolutional neural networks (CNNs) have …

Cancer is known as emperor of all maladies. It's a group of disease known to be fatal for life
if not detected on time. The disease originates in one cell and spreads slowly. Over a period …

Background: Breast cancer is one of the most lethal cancers among women. Early detection
and proper treatment reduce mortality rates. Histopathological images provide detailed …

Cancer decision-making is a complex process that can be exacerbated by the limited
availability of oncological expertise. This is particularly true in rural areas and settings with …