Mammogram-reading AI can detect breast cancer risk 5 years before onset

AI,artificial intelligence,breast cancer

AI,artificial intelligence,breast cancer

Screening for breast cancer has made a world of difference since free mammograms were first offered here around 20 years ago.

Artificial intelligence is powering an effort to detect breast cancer, a disease that kills more than 600 Kiwis each year. This could be the best step towards more consistent and reliable screening procedures.

For the study, the researchers used almost 90,000 complete-decision screening mammograms from approximately 40,000 ladies to train, validate and take a look at the deep mastering model. Traditional risk-prediction model only identified 18% of such patients.

Indeed, the team was able to create a model that could more effectively predict risk of breast cancer in patients.

Since the 1960s radiologists have noticed that women have unique and widely variable patterns of breast tissue visible on the mammogram...

Professor of radiology Constance Lehman from Harvard Medical School said in reference to this: "There's previously been minimal support in the medical community for screening strategies that are risk-based rather than age-based". "We can now leverage this detailed information to be more precise in our risk assessment at the individual woman level". Identifying patients at risk of developing breast cancer has therefore been a key focus for researchers looking to reduce the number of breast cancer-related deaths. Consequently, as confirmed by many previous studies such as those published in the Journal of Women's Health, it was more effective in predicting breast cancer for populations of White women than for Black or Hispanic women. The model was also equally accurate for patients of all races, notable because many traditional models have only been trained on white patients' data, leading to lower rates of detection in non-white populations. "If validated and made available for widespread use, this could really improve on our current strategies to estimate risk". But some of these factors are less correlated with breast cancer than others, harming the models' accuracy.

"The recent federal legislation that requires all women to be informed of their mammographic breast density is a strong message from Congress that women deserve access to their health information", says Lehman. In order to speed up the review of mammograms and enable objective assessment of risk, researchers have been working on developing computer models that can rapidly and reliably screen mammogram images for breast cancer risk.

The team aims to make their model a part of the standard of care. He also added, "By predicting who will develop cancer in the future, we can hopefully save lives and catch cancer before symptoms ever arise".