Mammographic breast tissue density is difficult to assess and quantify uniformly. In particular, BIRADS C and D density breasts are limited in distinguishing cancerous tissue from dense breast tissue by eye in this setting. The AI application automatically analyzes the image and generates a quantitative breast density assessment. In this way, AI provides radiologists with better diagnostic accuracy, especially for breasts with a higher proportion of glandular tissue, and reduces the variability of their opinions. Thus, it aids early diagnosis of breast cancer.
If cancer can be caught early, patients have up to a 99% chance of survival (Breast Cancer Early Detection - National Breast Cancer Foundation).
Thanks to artificial intelligence trained on tens of thousands of breast disease cases, various health problems can begin to be addressed early. This can lead to saving breast tissue.