Going deep: Artificial intelligence improves accuracy of breast ultrasound diagnoses

In 2020, the International Agency for Research on Cancer of the World Health Organization stated that breast cancer accounts for most cancer morbidities and mortalities in women worldwide. This alarming statistic not only necessitates newer methods for the early diagnosis of breast cancer, but also brings to light the importance of risk prediction of the occurrence and development of this disease. Ultrasound is an effective and noninvasive diagnostic procedure that truly saves lives; however, it is sometimes difficult for ultrasonologists to distinguish between malignant tumors and other types of benign growths. In particular, in China, breast masses are classified into four categories: benign tumors, malignant tumors, inflammatory masses, and adenosis (enlargement of milk-producing glands). When a benign breast mass is misdiagnosed as a malignant tumor, a biopsy usually follows, which puts the patient at unnecessary risk. The correct interpretation of ultrasound images is made even harder when factoring in the large workload of medical specialists.

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