INTEGRATING ARTIFICIAL INTELLIGENCE WITH MAMMOGRAPHY: A COMPLEMENTARY APPROACH IN THE DIAGNOSIS OF BREAST CANCER

Abstract

Screening mammography is a vital tool in the early detection of breast cancer, proven to reduce mortality associated with this disease. However, it faces challenges, such as limited sensitivity in cases of dense breast tissue and interpretative errors. The integration of artificial intelligence (AI) in mammographic interpretation appears as a promising solution to overcome these limitations, with recent studies demonstrating performance comparable to or superior to that of radiologists. This approach has the potential to improve early detection, increasing diagnostic reliability. Breast cancer is one of the leading causes of female mortality in the United States, requiring better detection methods. The integration of AI in breast radiology is essential to improve diagnosis and treatment. The review addresses applications, benefits and challenges of AI in clinical practice, emphasizing its importance as a complement to mammography. With continued development, it is expected to have a significant impact on women's health, saving lives and promoting more accurate diagnoses.