Breast cancer has been prevalent among females for some decades. However, it is the most pernicious cause of mortality among women worldwide — the data released by premier medical research organizations states so. “In 2020, there were 2.3 million women diagnosed with breast cancer and 685 000 deaths globally. As of 2020, 7.8 million women alive have been diagnosed with breast cancer in the past 5 years, making it the world’s most prevalent cancer,” the World Health Organisation (WHO) points out in its recent report on breast cancer. Early diagnosis is the only lifeguard — and employing machine learning in medical imaging can precede the path to wellness and reduced mortality rate. 

Since early detection of breast cancer is the only way to restore well-being, medical technology advancements can be brought well to the rescue. Integrating deep learning in medical image analysis has proven to be a game-changer in overpowering the diagnostic challenges cropping up during cancer treatment. Medical imaging technology that has been explicitly developed for detecting breast cancer symptoms at an earlier stage provides significant aid for the timely and accurate screening of breast cancer in women.