AI makes fewer mistakes than experienced radiologists and takes into account ethnic differences

AI makes fewer mistakes than experienced radiologists and takes into account ethnic differences

CureMetrix: AI provides an equalization of care across countries. A well-trained algorithm that has been trained on a variety of dense breasts, across different ethnicities, provides a significant advantage to a general radiologist


Breast cancer remains an acute and most urgent problem. In the United States, the number of diagnosed breast cancer cases increased by 28.7% in 2020. The World Health Organization (WHO) has officially recognized breast cancer as the most common type of cancer in the world.


Kevin Harris, president of CureMetrix, Inc., said in an interview that there are some racial and ethnic groups that are statistically more likely to develop breast cancer. In addition, some physiological differences in these groups make it difficult to diagnose breast cancer.


Therefore, CureMetrix developed cmTriage™, the first FDA-cleared mammography triage AI program, and diagnostic software cmAssist™ by training their algorithms on mammogram images from women worldwide in order to provide that service to radiologists.


Kevin Harris believes that AI can help solve the problem of inequality in access to health care in the United States and around the world.


For example, there may be cultural or religious issues that prevent women from undergoing routine mammograms. In these situations, it is possible to create mammography clinics that can be fully staffed by female radiology technicians who will use AI-based CAD to identify suspicious cases.


Moreover, the initial screening using the CAD algorithm will save women money.


According to the American Cancer Society, mammography is imperfect and does not allow radiologists to detect about 20% of cases of the disease. At the same time, more than half of the ..