Among all cancer types, breast cancer is the most prevalent. For females, it ranks as the second most common cause of cancer-related mortality. Every 1 person per 28 people in lifetime have a chance of developing breast cancer, according to statistics. Each year, it is estimated that over two million women encounter it. The high-risk group in India has an average age of 43–46 years, but in the west, women between the ages of 53 and 57 are more likely to get breast cancer. While there is no known cure for breast cancer, early detection and diagnosis significantly improves chances of survival. Treatment for breast cancer patients may be possible if the disease is identified and diagnosed early. Diagnosing benign from malignant tumours and determining whether a breast cancer case is early or progressed presents a number of challenges for cancer researchers. This study compares many methods for detecting breast cancer and provides a detailed analysis of each, highlighting the methods that are most accurate and economical. This study's primary goal is to comprehend the fundamental principles behind the various technologies used in breast cancer diagnosis. It is simple to save lives by spreading awareness of the latest and most varied detection and screening techniques.

Breast Cancer detection mammography Machine Learning Image processing Mortality Signal Processing Artificial Intelligence